Aplicaciones de la inteligencia artificial en la medicina

Briganti G, Le Moine O. Artificial Intelligence in Medicine: Today and Tomorrow. Front Med [Internet]. 2020 [citado 8 de octubre de 2022];7. Disponible en: https://www.frontiersin.org/articles/10.3389/fmed.2020.00027

Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc. 2020;92(4):807-12. doi: 10.1016/j.gie.2020.06.040

Huang Z, Chan TM, Dong W. MACE prediction of acute coronary syndrome via boosted resampling classification using electronic medical records. J Biomed Inform. 2017;66:161-70. doi: 10.1016/j.jbi.2017.01.001

Topalovic M, Das N, Burgel PR, Daenen M, Derom E, Haenebalcke C, et al. Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests. Eur Respir J [Internet]. 1 de abril de 2019 [citado 8 de octubre de 2022];53(4). Disponible en: https://erj.ersjournals.com/content/53/4/1801660

Lawton J, Blackburn M, Allen J, Campbell F, Elleri D, Leelarathna L, et al. Patients’ and caregivers’ experiences of using continuous glucose monitoring to support diabetes self-management: qualitative study. BMC Endocr Disord. 2018;18(1):12. doi: 10.1186/s12902-018-0239-1

Niel O, Boussard C, Bastard P. Artificial Intelligence Can Predict GFR Decline During the Course of ADPKD. Am J Kidney Dis. 2018;71(6):911-2. doi: 10.1053/j.ajkd.2018.01.051

Yang YJ, Bang CS. Application of artificial intelligence in gastroenterology. World J Gastroenterol. 2019;25(14):1666-83. doi: 10.3748/wjg.v25.i14.1666

Fernández-Esparrach G, Bernal J, López-Cerón M, Córdova H, Sánchez-Montes C, Miguel CR de, et al. Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps. Endoscopy. 2016;48(9):837-42. doi: 10.1055/s-0042-108434

Regalia G, Onorati F, Lai M, Caborni C, Picard RW. Multimodal wrist-worn devices for seizure detection and advancing research: Focus on the Empatica wristbands. Epilepsy Res. 2019;153:79-82. doi: 10.1016/j.eplepsyres.2019.02.007

Campanella G, Hanna MG, Geneslaw L, Miraflor A, Werneck Krauss Silva V, Busam KJ, et al. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nat Med. 2019;25(8):1301-9. doi: 10.1038/s41591-019-0508-1

Liu X, Faes L, Kale AU, Wagner SK, Fu DJ, Bruynseels A, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. Lancet Digit Health. 2019;1(6):e271-97. doi: 10.1016/S2589-7500(19)30123-2

Louis DN, Gerber GK, Baron JM, Bry L, Dighe AS, Getz G, et al. Computational Pathology: An Emerging Definition. Arch Pathol Lab Med. 2014;138(9):1133-8. doi: 10.1183/13993003.01660-2018

Herman DS, Rhoads DD, Schulz WL, Durant TJS. Artificial Intelligence and Mapping a New Direction in Laboratory Medicine: A Review. Clin Chem. 2021;67(11):1466-82. doi: 10.1093/clinchem/hvab165