machine learning

Shao Y, Zhang S, Raman VK, Patel SS, Cheng Y, Parulkar A, Lam PH, Moore H, Sheriff HM, Fonarow GC, Heidenreich PA, Wu WC, Ahmed[...]

Sant VR, Radhachandran A, Ivezic V, Lee DT, Livhits MJ, Wu JX, Masamed R, Arnold CW, Yeh MW, Speier W. From Bench-to-Bedside: How Artificial Intelligence[...]

Jawadi Z, He R, Srivastava PK, Fonarow GC, Khalil SO, Krishnan S, Eskin E, Chiang JN, Nsair A. Predicting in-hospital mortality among patients admitted with[...]

Goto R, Inoue K, Osawa I, Baicker K, Fleming SL, Tsugawa Y. Machine Learning Detects Heterogeneous Effects of Medicaid Coverage on Depression. Am J Epidemiol.[...]

Brunyé TT, Booth K, Hendel D, Kerr KF, Shucard H, Weaver DL, Elmore JG. Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies.[...]

Ha SM, Lin EY, Klausner JD, Adamson PC. Machine learning to predict ceftriaxone resistance using single nucleotide polymorphisms within a global database of Neisseria gonorrhoeae genomes. Microbiol[...]

Lee T, Lukac PJ, Vangala S, Kowsari K, Vu V, Fogelman S, Pfeffer MA, Bell DS. Evaluating the predictive ability of natural language processing in[...]

Hsu FC, Palmer ND, Chen SH, Ng MCY, Goodarzi MO, Rotter JI, Wagenknecht LE, Bancks MP, Bergman RN, Bowden DW. Methods for estimating insulin resistance[...]

Dey D, Arnaout R, Antani S, Badano A, Jacques L, Li H, Leiner T, Margerrison E, Samala R, Sengupta PP, Shah SJ, Slomka P, Williams[...]

Edgcomb JB, Tseng CH, Pan M, Klomhaus A, Zima BT. Assessing Detection of Children With Suicide-Related Emergencies: Evaluation and Development of Computable Phenotyping Approaches. JMIR[...]