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Trabalho de evento-resumo
Transforming standard RGB images in 3D digital phantoms for Monte Carlo simulations (2024)
Garcia, Marlon Rodrigues ; Palamoni, Otávio Perez; Moriyama, Lilian Tan
Source: Program. Conference titles: International Laser Physics Workshop - LPHYS'24. Unidade: IFSC
Subjects: IMAGEM 3D, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL, SIMULAÇÃO, MÉTODO DE MONTE CARLO
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GARCIA, Marlon Rodrigues e PALAMONI, Otávio Perez e MORIYAMA, Lilian Tan. Transforming standard RGB images in 3D digital phantoms for Monte Carlo simulations. 2024, Anais.. Bristol: Institute of Physics - IOP, 2024. Disponível em: https://www.lasphys.com/workshops/abstracts/files/2024/63/d0/25/742f3bbd6d6198460578104690/abstract.pdf. Acesso em: 03 out. 2024.
APA
Garcia, M. R., Palamoni, O. P., & Moriyama, L. T. (2024). Transforming standard RGB images in 3D digital phantoms for Monte Carlo simulations. In Program. Bristol: Institute of Physics - IOP. Recuperado de https://www.lasphys.com/workshops/abstracts/files/2024/63/d0/25/742f3bbd6d6198460578104690/abstract.pdf
NLM
Garcia MR, Palamoni OP, Moriyama LT. Transforming standard RGB images in 3D digital phantoms for Monte Carlo simulations [Internet]. Program. 2024 ;[citado 2024 out. 03 ] Available from: https://www.lasphys.com/workshops/abstracts/files/2024/63/d0/25/742f3bbd6d6198460578104690/abstract.pdf
Vancouver
Garcia MR, Palamoni OP, Moriyama LT. Transforming standard RGB images in 3D digital phantoms for Monte Carlo simulations [Internet]. Program. 2024 ;[citado 2024 out. 03 ] Available from: https://www.lasphys.com/workshops/abstracts/files/2024/63/d0/25/742f3bbd6d6198460578104690/abstract.pdf
Artigo de periodico
Hematopoietic colony-stimulating factors in head and neck cancers: Recent advances and therapeutic challenges (2024)
Vieira, Gustavo de Souza; Kimura, Talita de Carvalho ; Scarini, João Figueira ; Lima-Souza, Reydson Alcides de ; Lavareze, Luccas ; Emerick, Carolina ; Goncalves, Mayara Trevizol; Damas, Ingrid Iara; Figueiredo-Maciel, Tayná; Sá, Raisa Sales de; Kowalski, Luiz Paulo
Source: CYTOKINE.
Subjects: APRENDIZAGEM PROFUNDA, AMELOBLASTO, AMELOBLASTOMA, INTELIGÊNCIA ARTIFICIAL, TUMORES ODONTOGÊNICOS
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VIEIRA, Gustavo de Souza et al. Hematopoietic colony-stimulating factors in head and neck cancers: Recent advances and therapeutic challenges. CYTOKINE, v. 173, 2024Tradução . . Disponível em: https://observatorio.fm.usp.br/handle/OPI/57805. Acesso em: 03 out. 2024.
APA
Vieira, G. de S., Kimura, T. de C., Scarini, J. F., Lima-Souza, R. A. de, Lavareze, L., Emerick, C., et al. (2024). Hematopoietic colony-stimulating factors in head and neck cancers: Recent advances and therapeutic challenges. CYTOKINE, 173. doi:10.1016/j.cyto.2023.156417
NLM
Vieira G de S, Kimura T de C, Scarini JF, Lima-Souza RA de, Lavareze L, Emerick C, Goncalves MT, Damas II, Figueiredo-Maciel T, Sá RS de, Kowalski LP. Hematopoietic colony-stimulating factors in head and neck cancers: Recent advances and therapeutic challenges [Internet]. CYTOKINE. 2024 ; 173[citado 2024 out. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/57805
Vancouver
Vieira G de S, Kimura T de C, Scarini JF, Lima-Souza RA de, Lavareze L, Emerick C, Goncalves MT, Damas II, Figueiredo-Maciel T, Sá RS de, Kowalski LP. Hematopoietic colony-stimulating factors in head and neck cancers: Recent advances and therapeutic challenges [Internet]. CYTOKINE. 2024 ; 173[citado 2024 out. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/57805
Artigo de periodico
Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach (2024)
Gul, Saima; Hussain, Sajjad ; Khan, Hammad ; Arshad, Muhammad; Khan, Javaid Rabbani ; Motheo, Artur de Jesus
Source: Chemosphere. Unidade: IQSC
Subjects: INTELIGÊNCIA ARTIFICIAL, REDES NEURAIS, ANTIBIÓTICOS
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GUL, Saima et al. Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach. Chemosphere, v. 357, p. 141868, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.chemosphere.2024.141868. Acesso em: 03 out. 2024.
APA
Gul, S., Hussain, S., Khan, H., Arshad, M., Khan, J. R., & Motheo, A. de J. (2024). Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach. Chemosphere, 357, 141868. doi:10.1016/j.chemosphere.2024.141868
NLM
Gul S, Hussain S, Khan H, Arshad M, Khan JR, Motheo A de J. Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach [Internet]. Chemosphere. 2024 ; 357 141868.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.chemosphere.2024.141868
Vancouver
Gul S, Hussain S, Khan H, Arshad M, Khan JR, Motheo A de J. Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach [Internet]. Chemosphere. 2024 ; 357 141868.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.chemosphere.2024.141868
Artigo de periodico
AI is a viable alternative to high throughput screening: a 318-target study (2024)
Wallach, Izhar; Andricopulo, Adriano Defini ; Souza, Guilherme Eduardo de ; Valli, Marilia ; Guido, Rafael Victorio Carvalho ; Debonsi, Hosana Maria ; Teixeira, Thaiz Rodrigues
Source: Scientific Reports. Unidades: IFSC, FCFRP
Subjects: INTELIGÊNCIA ARTIFICIAL, PLANEJAMENTO DE FÁRMACOS, CRISTALOGRAFIA DE RAIOS X, REDES NEURAIS
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WALLACH, Izhar et al. AI is a viable alternative to high throughput screening: a 318-target study. Scientific Reports, v. 14, 2024Tradução . . Disponível em: https://doi.org/10.1038/s41598-024-54655-z. Acesso em: 03 out. 2024.
APA
Wallach, I., Andricopulo, A. D., Souza, G. E. de, Valli, M., Guido, R. V. C., Debonsi, H. M., & Teixeira, T. R. (2024). AI is a viable alternative to high throughput screening: a 318-target study. Scientific Reports, 14. doi:10.1038/s41598-024-54655-z
NLM
Wallach I, Andricopulo AD, Souza GE de, Valli M, Guido RVC, Debonsi HM, Teixeira TR. AI is a viable alternative to high throughput screening: a 318-target study [Internet]. Scientific Reports. 2024 ; 14[citado 2024 out. 03 ] Available from: https://doi.org/10.1038/s41598-024-54655-z
Vancouver
Wallach I, Andricopulo AD, Souza GE de, Valli M, Guido RVC, Debonsi HM, Teixeira TR. AI is a viable alternative to high throughput screening: a 318-target study [Internet]. Scientific Reports. 2024 ; 14[citado 2024 out. 03 ] Available from: https://doi.org/10.1038/s41598-024-54655-z
Trabalho de evento-resumo
Development of a machine learning model for predicting photophysical parameters of organic molecules (2024)
Araujo, João Marcos Rigon
Source: Program. Conference titles: International Laser Physics Workshop - LPHYS'24. Unidade: IFSC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, FÍSICA MOLECULAR
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ARAUJO, João Marcos Rigon. Development of a machine learning model for predicting photophysical parameters of organic molecules. 2024, Anais.. Bristol: Institute of Physics - IOP, 2024. Disponível em: https://www.lasphys.com/workshops/abstracts/files/2024/78/9a/9e/6d4b24912bf60a4d47a61349c7/abstract.pdf. Acesso em: 03 out. 2024.
APA
Araujo, J. M. R. (2024). Development of a machine learning model for predicting photophysical parameters of organic molecules. In Program. Bristol: Institute of Physics - IOP. Recuperado de https://www.lasphys.com/workshops/abstracts/files/2024/78/9a/9e/6d4b24912bf60a4d47a61349c7/abstract.pdf
NLM
Araujo JMR. Development of a machine learning model for predicting photophysical parameters of organic molecules [Internet]. Program. 2024 ;[citado 2024 out. 03 ] Available from: https://www.lasphys.com/workshops/abstracts/files/2024/78/9a/9e/6d4b24912bf60a4d47a61349c7/abstract.pdf
Vancouver
Araujo JMR. Development of a machine learning model for predicting photophysical parameters of organic molecules [Internet]. Program. 2024 ;[citado 2024 out. 03 ] Available from: https://www.lasphys.com/workshops/abstracts/files/2024/78/9a/9e/6d4b24912bf60a4d47a61349c7/abstract.pdf
Artigo de periodico
Thermal signature: a method to extract characteristics from infrared thermography data applied to the development of animal heat stress classifier models (2023)
Rodrigues, Alex Vinícius da Silva ; Martello, Luciane Silva ; Pacheco, Verônica Madeira ; Sardinha, Edson José de Souza ; Pereira, André Levi Viana; Sousa, Rafael Vieira de
Source: Journal of Thermal Biology. Unidade: FZEA
Subjects: TERMOGRAFIA, BEM-ESTAR DO ANIMAL, MINERAÇÃO DE DADOS, INTELIGÊNCIA ARTIFICIAL
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RODRIGUES, Alex Vinícius da Silva et al. Thermal signature: a method to extract characteristics from infrared thermography data applied to the development of animal heat stress classifier models. Journal of Thermal Biology, v. 115, p. 1-8, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.jtherbio.2023.103609. Acesso em: 03 out. 2024.
APA
Rodrigues, A. V. da S., Martello, L. S., Pacheco, V. M., Sardinha, E. J. de S., Pereira, A. L. V., & Sousa, R. V. de. (2023). Thermal signature: a method to extract characteristics from infrared thermography data applied to the development of animal heat stress classifier models. Journal of Thermal Biology, 115, 1-8. doi:10.1016/j.jtherbio.2023.103609
NLM
Rodrigues AV da S, Martello LS, Pacheco VM, Sardinha EJ de S, Pereira ALV, Sousa RV de. Thermal signature: a method to extract characteristics from infrared thermography data applied to the development of animal heat stress classifier models [Internet]. Journal of Thermal Biology. 2023 ; 115 1-8.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.jtherbio.2023.103609
Vancouver
Rodrigues AV da S, Martello LS, Pacheco VM, Sardinha EJ de S, Pereira ALV, Sousa RV de. Thermal signature: a method to extract characteristics from infrared thermography data applied to the development of animal heat stress classifier models [Internet]. Journal of Thermal Biology. 2023 ; 115 1-8.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.jtherbio.2023.103609
Artigo de periodico
Treatment of fungal infection on left ventricle assist device driveline exit site: a case report and systematic review (2023)
Brandao, Sara Michelly Goncalves; Biseli, Bruno; Ayub-Ferreira, Silvia Moreira; Strabelli, Tania Mara Varejao; Bocchi, Edimar Alcides
Source: Journal of wound care. Unidade: FM
Subjects: REVISÃO SISTEMÁTICA, INSUFICIÊNCIA CARDÍACA, INTELIGÊNCIA ARTIFICIAL
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BRANDAO, Sara Michelly Goncalves et al. Treatment of fungal infection on left ventricle assist device driveline exit site: a case report and systematic review. Journal of wound care, v. 32, 2023Tradução . . Disponível em: https://observatorio.fm.usp.br/handle/OPI/57370. Acesso em: 03 out. 2024.
APA
Brandao, S. M. G., Biseli, B., Ayub-Ferreira, S. M., Strabelli, T. M. V., & Bocchi, E. A. (2023). Treatment of fungal infection on left ventricle assist device driveline exit site: a case report and systematic review. Journal of wound care, 32. doi:10.12968/jowc.2023.32.Sup9a.cxc
NLM
Brandao SMG, Biseli B, Ayub-Ferreira SM, Strabelli TMV, Bocchi EA. Treatment of fungal infection on left ventricle assist device driveline exit site: a case report and systematic review [Internet]. Journal of wound care. 2023 ; 32[citado 2024 out. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/57370
Vancouver
Brandao SMG, Biseli B, Ayub-Ferreira SM, Strabelli TMV, Bocchi EA. Treatment of fungal infection on left ventricle assist device driveline exit site: a case report and systematic review [Internet]. Journal of wound care. 2023 ; 32[citado 2024 out. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/57370
Artigo de periodico
Artificial intelligence in single screw polymer extrusion: learning from computational data (2022)
Gaspar-Cunha, António ; Monaco, Francisco José ; Sikora, Janusz ; Delbem, Alexandre Cláudio Botazzo
Source: Engineering Applications of Artificial Intelligence. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS, EXTRUSÃO
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GASPAR-CUNHA, António et al. Artificial intelligence in single screw polymer extrusion: learning from computational data. Engineering Applications of Artificial Intelligence, v. 116, p. 1-20, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.engappai.2022.105397. Acesso em: 03 out. 2024.
APA
Gaspar-Cunha, A., Monaco, F. J., Sikora, J., & Delbem, A. C. B. (2022). Artificial intelligence in single screw polymer extrusion: learning from computational data. Engineering Applications of Artificial Intelligence, 116, 1-20. doi:10.1016/j.engappai.2022.105397
NLM
Gaspar-Cunha A, Monaco FJ, Sikora J, Delbem ACB. Artificial intelligence in single screw polymer extrusion: learning from computational data [Internet]. Engineering Applications of Artificial Intelligence. 2022 ; 116 1-20.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.engappai.2022.105397
Vancouver
Gaspar-Cunha A, Monaco FJ, Sikora J, Delbem ACB. Artificial intelligence in single screw polymer extrusion: learning from computational data [Internet]. Engineering Applications of Artificial Intelligence. 2022 ; 116 1-20.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.engappai.2022.105397
Artigo de periodico
Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management (2022)
Levin, Anna Sara ; Freire, Maristela P ; Oliveira, Maura Salaroli de ; Nastri, Ana Catharina de Seixas Santos ; Harima, Leila; Perdigão Neto, Lauro Vieira ; Magri, Marcello M; Fialkovitz, Gabriel ; Figueiredo, Pedro H. M. F; Siciliano, Rinaldo Focaccia ; Sabino, Ester Cerdeira ; Carlotti, Danilo Panzeri ; Rodrigues, Davi Silva ; Nunes, Fátima L S; Ferreira, João Eduardo
Source: BMC Medical Informatics and Decision Making. Unidades: FM, IME
Subjects: COVID-19, HOSPITALIZAÇÃO, PROGNÓSTICO, INTELIGÊNCIA ARTIFICIAL
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LEVIN, Anna Sara et al. Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management. BMC Medical Informatics and Decision Making, v. 22, n. 1, 2022Tradução . . Disponível em: https://doi.org/10.1186/s12911-022-01983-7. Acesso em: 03 out. 2024.
APA
Levin, A. S., Freire, M. P., Oliveira, M. S. de, Nastri, A. C. de S. S., Harima, L., Perdigão Neto, L. V., et al. (2022). Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management. BMC Medical Informatics and Decision Making, 22( 1). doi:10.1186/s12911-022-01983-7
NLM
Levin AS, Freire MP, Oliveira MS de, Nastri AC de SS, Harima L, Perdigão Neto LV, Magri MM, Fialkovitz G, Figueiredo PHMF, Siciliano RF, Sabino EC, Carlotti DP, Rodrigues DS, Nunes FLS, Ferreira JE. Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management [Internet]. BMC Medical Informatics and Decision Making. 2022 ; 22( 1):[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s12911-022-01983-7
Vancouver
Levin AS, Freire MP, Oliveira MS de, Nastri AC de SS, Harima L, Perdigão Neto LV, Magri MM, Fialkovitz G, Figueiredo PHMF, Siciliano RF, Sabino EC, Carlotti DP, Rodrigues DS, Nunes FLS, Ferreira JE. Correlating drug prescriptions with prognosis in severe COVID-19: first step towards resource management [Internet]. BMC Medical Informatics and Decision Making. 2022 ; 22( 1):[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s12911-022-01983-7
Artigo de periodico
The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study (2022)
Kudo, Maira Suzuka; Souza, Vinicius Meneguette Gomes de; Estivallet, Carmen Liane Neubarth; Amorim, Henrique Alves de; Kim, Fernando J; Leite, Katia Ramos Moreira ; Moraes, Matheus Cardoso
Source: Patient safety in surgery. Unidade: FM
Subjects: INTELIGÊNCIA ARTIFICIAL, NEOPLASIAS PROSTÁTICAS, PROSTATECTOMIA
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ABNT
KUDO, Maira Suzuka et al. The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study. Patient safety in surgery, v. 16, n. 1, 2022Tradução . . Disponível em: https://doi.org/10.1186/s13037-022-00345-6. Acesso em: 03 out. 2024.
APA
Kudo, M. S., Souza, V. M. G. de, Estivallet, C. L. N., Amorim, H. A. de, Kim, F. J., Leite, K. R. M., & Moraes, M. C. (2022). The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study. Patient safety in surgery, 16( 1). doi:10.1186/s13037-022-00345-6
NLM
Kudo MS, Souza VMG de, Estivallet CLN, Amorim HA de, Kim FJ, Leite KRM, Moraes MC. The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study [Internet]. Patient safety in surgery. 2022 ; 16( 1):[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s13037-022-00345-6
Vancouver
Kudo MS, Souza VMG de, Estivallet CLN, Amorim HA de, Kim FJ, Leite KRM, Moraes MC. The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study [Internet]. Patient safety in surgery. 2022 ; 16( 1):[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s13037-022-00345-6
Artigo de periodico
What is it about humanity that we can’t give away to intelligent machines? A European perspective (2021)
Coombs, Crispin ; Stacey, Patrick ; Kawalek, Peter; Simeonova, Boyka; Becker, Joerg; Bergener, Katrin; Carvalho, João Álvaro ; Fantinato, Marcelo ; Garmann-Johnsen, Niels Frederik; Grimme, Christian; Stein, Armin ; Trautmann, Heike
Source: International Journal of Information Management. Unidade: EACH
Subjects: INTELIGÊNCIA ARTIFICIAL, ROBÔS
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COOMBS, Crispin et al. What is it about humanity that we can’t give away to intelligent machines? A European perspective. International Journal of Information Management, v. 58, n. ju 2021, p. 01-13, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.ijinfomgt.2021.102311. Acesso em: 03 out. 2024.
APA
Coombs, C., Stacey, P., Kawalek, P., Simeonova, B., Becker, J., Bergener, K., et al. (2021). What is it about humanity that we can’t give away to intelligent machines? A European perspective. International Journal of Information Management, 58( ju 2021), 01-13. doi:10.1016/j.ijinfomgt.2021.102311
NLM
Coombs C, Stacey P, Kawalek P, Simeonova B, Becker J, Bergener K, Carvalho JÁ, Fantinato M, Garmann-Johnsen NF, Grimme C, Stein A, Trautmann H. What is it about humanity that we can’t give away to intelligent machines? A European perspective [Internet]. International Journal of Information Management. 2021 ; 58( ju 2021): 01-13.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.ijinfomgt.2021.102311
Vancouver
Coombs C, Stacey P, Kawalek P, Simeonova B, Becker J, Bergener K, Carvalho JÁ, Fantinato M, Garmann-Johnsen NF, Grimme C, Stein A, Trautmann H. What is it about humanity that we can’t give away to intelligent machines? A European perspective [Internet]. International Journal of Information Management. 2021 ; 58( ju 2021): 01-13.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.ijinfomgt.2021.102311
Artigo de periodico
Untangling hybrid hydrological models with explainable artificial intelligence (2021)
Althoff, Daniel; Bazame, Helizani Couto ; Nascimento, Jessica Garcia
Source: H2Open Journal. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, HIDROLOGIA, INTELIGÊNCIA ARTIFICIAL
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ABNT
ALTHOFF, Daniel e BAZAME, Helizani Couto e NASCIMENTO, Jessica Garcia. Untangling hybrid hydrological models with explainable artificial intelligence. H2Open Journal, v. 4, n. 4, p. 13-28, 2021Tradução . . Disponível em: https://doi.org/10.2166/h2oj.2021.066. Acesso em: 03 out. 2024.
APA
Althoff, D., Bazame, H. C., & Nascimento, J. G. (2021). Untangling hybrid hydrological models with explainable artificial intelligence. H2Open Journal, 4( 4), 13-28. doi:10.2166/h2oj.2021.066
NLM
Althoff D, Bazame HC, Nascimento JG. Untangling hybrid hydrological models with explainable artificial intelligence [Internet]. H2Open Journal. 2021 ; 4( 4): 13-28.[citado 2024 out. 03 ] Available from: https://doi.org/10.2166/h2oj.2021.066
Vancouver
Althoff D, Bazame HC, Nascimento JG. Untangling hybrid hydrological models with explainable artificial intelligence [Internet]. H2Open Journal. 2021 ; 4( 4): 13-28.[citado 2024 out. 03 ] Available from: https://doi.org/10.2166/h2oj.2021.066
Artigo de periodico
Neonatal mortality prediction with routinely collected data: a machine learning approach (2021)
Batista, André Filipe de Moraes; Diniz, Carmen Simone Grilo ; Bonilha, Eliana de Aquino; Kawachi, Ichiro; Chiavegatto Filho, Alexandre Dias Porto
Source: BMC Pediatrics. Unidade: FSP
Subjects: MORTALIDADE NEONATAL, INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, NASCIMENTO, PREDIÇÃO, BRASIL
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ABNT
BATISTA, André Filipe de Moraes et al. Neonatal mortality prediction with routinely collected data: a machine learning approach. BMC Pediatrics, v. 21, p. art. 322 [6], 2021Tradução . . Disponível em: https://doi.org/10.1186/s12887-021-02788-9. Acesso em: 03 out. 2024.
APA
Batista, A. F. de M., Diniz, C. S. G., Bonilha, E. de A., Kawachi, I., & Chiavegatto Filho, A. D. P. (2021). Neonatal mortality prediction with routinely collected data: a machine learning approach. BMC Pediatrics, 21, art. 322 [6]. doi:10.1186/s12887-021-02788-9
NLM
Batista AF de M, Diniz CSG, Bonilha E de A, Kawachi I, Chiavegatto Filho ADP. Neonatal mortality prediction with routinely collected data: a machine learning approach [Internet]. BMC Pediatrics. 2021 ; 21 art. 322 [6].[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s12887-021-02788-9
Vancouver
Batista AF de M, Diniz CSG, Bonilha E de A, Kawachi I, Chiavegatto Filho ADP. Neonatal mortality prediction with routinely collected data: a machine learning approach [Internet]. BMC Pediatrics. 2021 ; 21 art. 322 [6].[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s12887-021-02788-9
Trabalho de evento-anais periodico
Operation of Neuronal Membrane Simulator Circuit for Tests with Memristor Based on Graphene and Graphene Oxide (2021)
Sparvoli, Marina; Marma, Jonas S.; Nunes, Gabriel F.; Jorge, Fábio de Oliveira
Source: Advances in Computational Intelligence (IWANN 2021), PT II. Conference titles: International Conference on Quantitative Evaluation Systems (QEST). Unidade: IF
Subjects: CIÊNCIA DA COMPUTAÇÃO, INTELIGÊNCIA ARTIFICIAL, REDES NEURAIS, NEUROTRANSMISSORES, CAPACITORES
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ABNT
SPARVOLI, Marina et al. Operation of Neuronal Membrane Simulator Circuit for Tests with Memristor Based on Graphene and Graphene Oxide. Advances in Computational Intelligence (IWANN 2021), PT II. Londres: Instituto de Física, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/978-3-030-85099-9_8. Acesso em: 03 out. 2024. , 2021
APA
Sparvoli, M., Marma, J. S., Nunes, G. F., & Jorge, F. de O. (2021). Operation of Neuronal Membrane Simulator Circuit for Tests with Memristor Based on Graphene and Graphene Oxide. Advances in Computational Intelligence (IWANN 2021), PT II. Londres: Instituto de Física, Universidade de São Paulo. doi:10.1007/978-3-030-85099-9_8
NLM
Sparvoli M, Marma JS, Nunes GF, Jorge F de O. Operation of Neuronal Membrane Simulator Circuit for Tests with Memristor Based on Graphene and Graphene Oxide [Internet]. Advances in Computational Intelligence (IWANN 2021), PT II. 2021 ; 12862 93-102.[citado 2024 out. 03 ] Available from: https://doi.org/10.1007/978-3-030-85099-9_8
Vancouver
Sparvoli M, Marma JS, Nunes GF, Jorge F de O. Operation of Neuronal Membrane Simulator Circuit for Tests with Memristor Based on Graphene and Graphene Oxide [Internet]. Advances in Computational Intelligence (IWANN 2021), PT II. 2021 ; 12862 93-102.[citado 2024 out. 03 ] Available from: https://doi.org/10.1007/978-3-030-85099-9_8
Artigo de periodico
Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality (2021)
Bianchini, Vitor de Jesus Martins ; Mascarin, Gabriel Moura ; Silva, Lúcia Cristina Aparecida Santos; Arthur, Valter ; Carstensen, Jens Michael ; Boelt, Birte ; Silva, Clíssia Barboza da
Source: Plant Methods. Unidades: CENA, ESALQ
Subjects: ESPECTROSCOPIA, INTELIGÊNCIA ARTIFICIAL, PINHÃO MANSO, RADIOGRAFIA, SEMENTES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIANCHINI, Vitor de Jesus Martins et al. Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality. Plant Methods, v. 17, n. 9, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1186/s13007-021-00709-6. Acesso em: 03 out. 2024.
APA
Bianchini, V. de J. M., Mascarin, G. M., Silva, L. C. A. S., Arthur, V., Carstensen, J. M., Boelt, B., & Silva, C. B. da. (2021). Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality. Plant Methods, 17( 9), 1-13. doi:10.1186/s13007-021-00709-6
NLM
Bianchini V de JM, Mascarin GM, Silva LCAS, Arthur V, Carstensen JM, Boelt B, Silva CB da. Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality [Internet]. Plant Methods. 2021 ; 17( 9): 1-13.[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s13007-021-00709-6
Vancouver
Bianchini V de JM, Mascarin GM, Silva LCAS, Arthur V, Carstensen JM, Boelt B, Silva CB da. Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality [Internet]. Plant Methods. 2021 ; 17( 9): 1-13.[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s13007-021-00709-6
Artigo de periodico
Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging (2020)
Faleiros, Matheus Calil; Nogueira-Barbosa, Marcello Henrique ; Dalto, Vitor Faeda ; Júnior, José Raniery Ferreira ; Tenório, Ariane Priscilla Magalhães; Luppino-Assad, Rodrigo; Louzada Júnior, Paulo ; Rangayyan, Rangaraj Mandayam; Azevedo-Marques, Paulo Mazzoncini de
Source: Advances in Rheumatology. Unidade: FMRP
Subjects: DIAGNÓSTICO POR COMPUTADOR, ARTICULAÇÕES, DOENÇAS REUMÁTICAS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FALEIROS, Matheus Calil et al. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. Advances in Rheumatology, v. 60, p. 1-10, 2020Tradução . . Disponível em: https://doi.org/10.1186/s42358-020-00126-8. Acesso em: 03 out. 2024.
APA
Faleiros, M. C., Nogueira-Barbosa, M. H., Dalto, V. F., Júnior, J. R. F., Tenório, A. P. M., Luppino-Assad, R., et al. (2020). Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. Advances in Rheumatology, 60, 1-10. doi:10.1186/s42358-020-00126-8
NLM
Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada Júnior P, Rangayyan RM, Azevedo-Marques PM de. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging [Internet]. Advances in Rheumatology. 2020 ; 60 1-10.[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s42358-020-00126-8
Vancouver
Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada Júnior P, Rangayyan RM, Azevedo-Marques PM de. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging [Internet]. Advances in Rheumatology. 2020 ; 60 1-10.[citado 2024 out. 03 ] Available from: https://doi.org/10.1186/s42358-020-00126-8
Artigo de periodico-carta/editorial
From chemoinformatics to deep learning: an open road to drug discovery. [Editorial] (2019)
Ferreira, Leonardo Luiz Gomes ; Andricopulo, Adriano Defini
Source: Future Medicinal Chemistry. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERREIRA, Leonardo Luiz Gomes e ANDRICOPULO, Adriano Defini. From chemoinformatics to deep learning: an open road to drug discovery. [Editorial]. Future Medicinal Chemistry. London: Instituto de Física de São Carlos, Universidade de São Paulo. Disponível em: https://doi.org/10.4155/fmc-2018-0449. Acesso em: 03 out. 2024. , 2019
APA
Ferreira, L. L. G., & Andricopulo, A. D. (2019). From chemoinformatics to deep learning: an open road to drug discovery. [Editorial]. Future Medicinal Chemistry. London: Instituto de Física de São Carlos, Universidade de São Paulo. doi:10.4155/fmc-2018-0449
NLM
Ferreira LLG, Andricopulo AD. From chemoinformatics to deep learning: an open road to drug discovery. [Editorial] [Internet]. Future Medicinal Chemistry. 2019 ; 11( 5): 371-374.[citado 2024 out. 03 ] Available from: https://doi.org/10.4155/fmc-2018-0449
Vancouver
Ferreira LLG, Andricopulo AD. From chemoinformatics to deep learning: an open road to drug discovery. [Editorial] [Internet]. Future Medicinal Chemistry. 2019 ; 11( 5): 371-374.[citado 2024 out. 03 ] Available from: https://doi.org/10.4155/fmc-2018-0449
Parte de monografia/livro
Inconsistency measurement in probabilistic logic (2018)
De Bona, Glauber ; Finger, Marcelo ; Potyka, Nico; Thimm, Matthias
Source: Measuring inconsistency in information. Unidades: IME, EP
Subjects: LÓGICA, RACIOCÍNIO PROBABILÍSTICO, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DE BONA, Glauber et al. Inconsistency measurement in probabilistic logic. Measuring inconsistency in information. Tradução . London: College Publications, 2018. . Disponível em: http://www.mthimm.de/pub/2018/DeBona_2018.pdf. Acesso em: 03 out. 2024.
APA
De Bona, G., Finger, M., Potyka, N., & Thimm, M. (2018). Inconsistency measurement in probabilistic logic. In Measuring inconsistency in information. London: College Publications. Recuperado de http://www.mthimm.de/pub/2018/DeBona_2018.pdf
NLM
De Bona G, Finger M, Potyka N, Thimm M. Inconsistency measurement in probabilistic logic [Internet]. In: Measuring inconsistency in information. London: College Publications; 2018. [citado 2024 out. 03 ] Available from: http://www.mthimm.de/pub/2018/DeBona_2018.pdf
Vancouver
De Bona G, Finger M, Potyka N, Thimm M. Inconsistency measurement in probabilistic logic [Internet]. In: Measuring inconsistency in information. London: College Publications; 2018. [citado 2024 out. 03 ] Available from: http://www.mthimm.de/pub/2018/DeBona_2018.pdf
Artigo de periodico
Forecasting stock market index daily direction: a Bayesian network approach (2018)
Malagrino, Luciana S.; Roman, Norton Trevisan; Monteiro, Ana M.
Source: Expert Systems with Applications: an international journal. Unidade: EACH
Subjects: INFERÊNCIA BAYESIANA, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MALAGRINO, Luciana S. e ROMAN, Norton Trevisan e MONTEIRO, Ana M. Forecasting stock market index daily direction: a Bayesian network approach. Expert Systems with Applications: an international journal, v. 105, p. 11-22, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2018.03.039. Acesso em: 03 out. 2024.
APA
Malagrino, L. S., Roman, N. T., & Monteiro, A. M. (2018). Forecasting stock market index daily direction: a Bayesian network approach. Expert Systems with Applications: an international journal, 105, 11-22. doi:10.1016/j.eswa.2018.03.039
NLM
Malagrino LS, Roman NT, Monteiro AM. Forecasting stock market index daily direction: a Bayesian network approach [Internet]. Expert Systems with Applications: an international journal. 2018 ; 105 11-22.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.eswa.2018.03.039
Vancouver
Malagrino LS, Roman NT, Monteiro AM. Forecasting stock market index daily direction: a Bayesian network approach [Internet]. Expert Systems with Applications: an international journal. 2018 ; 105 11-22.[citado 2024 out. 03 ] Available from: https://doi.org/10.1016/j.eswa.2018.03.039
Artigo de periodico
Generating natural language descriptions using speaker-dependent information (2017)
Ferreira, Thiago Castro; Paraboni, Ivandré
Source: Natural Language Engineering. Unidade: EACH
Subjects: LINGUAGEM NATURAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERREIRA, Thiago Castro e PARABONI, Ivandré. Generating natural language descriptions using speaker-dependent information. Natural Language Engineering, v. 23, n. 6, p. 813-834, 2017Tradução . . Disponível em: https://doi.org/10.1017/S1351324917000079. Acesso em: 03 out. 2024.
APA
Ferreira, T. C., & Paraboni, I. (2017). Generating natural language descriptions using speaker-dependent information. Natural Language Engineering, 23( 6), 813-834. doi:10.1017/S1351324917000079
NLM
Ferreira TC, Paraboni I. Generating natural language descriptions using speaker-dependent information [Internet]. Natural Language Engineering. 2017 ; 23( 6):813-834.[citado 2024 out. 03 ] Available from: https://doi.org/10.1017/S1351324917000079
Vancouver
Ferreira TC, Paraboni I. Generating natural language descriptions using speaker-dependent information [Internet]. Natural Language Engineering. 2017 ; 23( 6):813-834.[citado 2024 out. 03 ] Available from: https://doi.org/10.1017/S1351324917000079

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