As the health care industry adopts artificial intelligence, machine learning, and other modeling techniques, it is seeing benefits to both patient outcomes and cost reduction; however, it needs to be cognizant of and ensure proper management of the r...
After working at Apple designing circuits and signal processing algorithms for products including the first iPad, Timnit Gebru (Figure 1) received her Ph.D. from the Stanford Artificial Intelligence Laboratory in the area of computer vision. She rece...
This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a deep learning–based signal generation pipeline to capture how patients describe cutaneous eruptions.
Studies in health technology and informatics
Jan 1, 2018
ICD encoded diagnoses are a popular criterion for eligibility algorithms for study cohort recruitment. However, "official" ICD encoded diagnoses used for billing purposes are afflicted with a bias originating from legal issues. This work presents an ...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide ex...
This study documents reporting errors in a sample of over 250,000 p-values reported in eight major psychology journals from 1985 until 2013, using the new R package "statcheck." statcheck retrieved null-hypothesis significance testing (NHST) results ...
As predicted by fuzzy-trace theory, people with a range of training—from untrained adolescents to expert physicians—are susceptible to biases and errors in judgment and perception of HIV-AIDS risk. To explain why this occurs, we introduce fuzzy-trace...