The complexity of transplant medicine pushes the boundaries of innate, human reasoning. From networks of immune modulators to dynamic pharmacokinetics to variable postoperative graft survival to equitable allocation of scarce organs, machine learning...
Advances in systems immunology, such as new biomarkers, offer the potential for highly personalized immunosuppression regimens that could improve patient outcomes. In the future, integrating all of this information with other patient history data wil...
Interdisciplinary sciences, computational life sciences
33886097
The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China, has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 million deaths across the globe. To combat the growing pandemic on urgent ba...
There has been an exponential growth of artificial intelligence (AI) and machine learning (ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has been mainly driven by the confluence of two factors: the advances ...
OBJECTIVE: To determine whether a machine learning causal inference model can optimize trigger injection timing to maximize the yield of fertilized oocytes (2PNs) and total usable blastocysts for a given cohort of stimulated follicles.
American journal of speech-language pathology
39173110
PURPOSE: This feasibility trial describes changes in rhotic production in residual speech sound disorder following ten 40-min sessions including artificial intelligence (AI)-assisted motor-based intervention with ChainingAI, a version of Speech Motor...
Although clinician-supported computer-assisted cognitive-behaviour therapy (CCBT) is well established as an effective treatment for depression and anxiety, less is known about the specific interventions used during coaching sessions that contribute t...