Results 201 to 210 of about 2,535,602 (380)

Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics

American Journal of Medical Genetics Part A, EarlyView.
ABSTRACT Artificial intelligence (AI) is rapidly transforming numerous aspects of daily life, including clinical practice and biomedical research. In light of this rapid transformation, and in the context of medical genetics, we assembled a group of leaders in the field to respond to the question about how AI is affecting, and especially how AI will ...
Benjamin D. Solomon, Morgan Cheatham, Thales A. C. de Guimarães, Dat Duong, Melissa A. Haendel, Tzung‐Chien Hsieh, Behnam Javanmardi, Britt Johnson, Peter Krawitz, Paul Kruszka, Tim Laurent, Ni‐Chung Lee, Kirsty McWalter, Michel Michaelides, Klaus Mohnike, Nikolas Pontikos, Maria J. Guillen Sacoto, Yousif J. Shwetar, Vincent D. Ustach, Rebekah L. Waikel, William Woof   +20 more
wiley   +1 more source

Faculty Opinions recommendation of Bootstrap, Bayesian probability and maximum likelihood mapping: exploring new tools for comparative genome analyses.

, 2002
Eugene Koonin
openalex   +1 more source

Phase II Trial Design with Bayesian Adaptive Randomization and Predictive Probability [PDF]

, 2012
Guosheng Yin, Nan Chen, J. Jack Lee
openalex   +1 more source

Opportunities in Middle Childhood: Multiple System Involvement During Middle Childhood and Early Adolescence in Northern Territory, Australia

Australian Journal of Social Issues, EarlyView.
ABSTRACT Middle childhood offers a crucial window to identify and support children at risk of adverse outcomes in adolescence. This retrospective cohort study examined how data from multiple systems could identify children with the greatest need for support during middle childhood and early adolescence. Using individual level linked records from health,
Vincent Yaofeng He, Jenny Williams, Steven Roche, Tamika Williams, Steven Guthridge   +4 more
wiley   +1 more source

Renal DCE-MRI Model Selection Using Bayesian Probability Theory. [PDF]

Tomography, 2015
Beeman SC, Osei-Owusu P, Duan C, Engelbach J, Bretthorst GL, Ackerman JJH, Blumer KJ, Garbow JR.   +7 more
europepmc   +1 more source

GABAergic modulation of beta power enhances motor adaptation in frontotemporal lobar degeneration

Alzheimer's &Dementia, Volume 21, Issue 5, May 2025.
Abstract INTRODUCTION We examined how abnormal prefrontal neurophysiology and changes in gamma‐aminobutyric acid‐ergic (GABAergic) neurotransmission contribute to behavioral impairments in disorders associated with frontotemporal lobar degeneration (FTLD). METHODS We recorded magnetoencephalography during an adaptive visuomotor task from 11 people with
Laura E. Hughes, Natalie E. Adams, Matthew A. Rouse, Michelle Naessens, Alexander Shaw, Alexander G. Murley, Thomas E. Cope, Negin Holland, David Nesbitt, Duncan Street, David J. Whiteside, James B. Rowe   +11 more
wiley   +1 more source

A Neural Bayesian Estimator for Conditional Probability Densities

, 2004
Michael Feindt
openalex   +2 more sources

Improving kernel incapability by equivalent probability in flexible naïve Bayesian [PDF]

, 2012
James N. K. Liu, Yulin He, Xizhao Wang
openalex   +1 more source

AI in Neurology: Everything, Everywhere, All at Once Part 3: Surveillance, Synthesis, Simulation, and Systems

Annals of Neurology, EarlyView.
This final part 3 review builds on the practical applications discussed in part 2 and explores how artificial intelligence (AI) is transforming data management, neurological education, and neurological care across large healthcare networks and datasets. The review also highlights AI's role in real‐world and synthetic data, digital twins, and innovative
Matthew Rizzo
wiley   +1 more source

Generating Conditional Probabilities for Bayesian Networks: Easing the Knowledge Acquisition Problem

, 2004
Balaram Das
openalex   +2 more sources