Results 111 to 120 of about 69,200 (270)

AI‐Driven Microphysiological Systems for Advancing Nanoparticle Therapeutics

Advanced Intelligent Systems, EarlyView.
This review outlines recent advances in integrating artificial intelligence with microphysiological systems for nanoparticle evaluation. It highlights data‐driven optimization, image‐based prediction, and AI‐enabled analysis frameworks that advance translational research and support the development of personalized nanomedicine. Nanoparticles (NPs) play
Yedam Lee, Jaehong Min, Sujin Kim, Jihoon Ko   +3 more
wiley   +1 more source

Mainstream Artificial Intelligence Technologies in Contemporary Ophthalmology

Advanced Intelligent Systems, EarlyView.
This review explores the latest artificial intelligence (AI) technologies in ophthalmology, focusing on four key data types: medical imaging, electronic health records, robotic‐assisted surgery, and genomics. It examines the structural features, use cases, clinical goals, and evaluation metrics of various AI algorithms, while also introducing emerging ...
Shiqi Yin, Lei Wang, Shanjun Wu, Jiewei Jiang, Wei Qiang, Yangyang Wang, Shihong Wang, Yi Shao, Wei Chen, Zhongwen Li   +9 more
wiley   +1 more source

Enhanced Embolic Signal Analysis through Ensemble Deep Learning Techniques Utilizing Transfer Learning and Layer Freezing Strategies

Advanced Intelligent Systems, EarlyView.
A 10‐convolutional neural network ensemble using transfer learning and layer freezing analyzes 400 Doppler‐ultrasound spectrograms to distinguish speckle, artifact, and ESs. Soft and hard voting drive performance to 96.7% accuracy and 96.5% F1, highlighting a practical route for early embolus detection and stroke‐risk mitigation.
M. Ikbal Karadeli, Berke Cansiz, Nizamettin Aydin, Gorkem Serbes   +3 more
wiley   +1 more source

MO‐hHHO: Multi‐Objective Hybrid Harris Hawks Optimization for Prediction of Coronary Artery Disease

Advanced Intelligent Systems, EarlyView.
This article proposes a novel Multi‐Objective hybrid Harris Hawks Optimization (MO‐hHHO) algorithm for simultaneous feature selection and hyperparameter tuning in heart disease classification. The approach leverages adaptive exploration‐exploitation strategies to enhance convergence efficiency.
Anu Ragavi Vijayaraj, Subbulakshmi Pasupathi   +1 more
wiley   +1 more source

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

Diagnostic Yield of Genome Sequencing Versus Exome Sequencing in Pediatric Patients With Rare Phenotypes: A Systematic Review and Meta‐Analysis

American Journal of Medical Genetics Part A, EarlyView.
ABSTRACT Rare diseases affect 6% of Western societies and are a leading cause of pediatric mortality. The popularization of Next Generation Sequencing technologies, especially exome sequencing (ES), revolutionized the diagnosis of children with rare disease. Still, most patients face extensive diagnostic odysseys and remain undiagnosed.
Anna Luiza Braga Albuquerque, Giovanna Giovacchini dos Santos, Sara Hadj Sadok, Breno Bopp Antonello, Lorena Melo de Jesus, Maria Eduarda Andrade de Carvalho, Antonio Mutarelli, Paulo Victor Zattar Ribeiro   +7 more
wiley   +1 more source

Evolution for our time: a theory of legal memetics [PDF]

The purpose of this paper is to explore the significance for legal thought of recent developments in evolutionary theory which are associated with the notion of 'memetics'.
Simon Deakin
core  

Artificial Intelligence Software Changes Rare Disease Testing Strategy in Real Time: An International Case Series Using Face2Gene

American Journal of Medical Genetics Part A, EarlyView.
ABSTRACT Genetic disorders commonly share features such as developmental delays, cognitive impairment, and behavioral challenges, yet many conditions also present unique dysmorphic features that distinguish them. Performing a thorough medical and family history and a detailed physical exam with attention to dysmorphic features is often the first step ...
Natasha L. Rudy, Adriana Gomes, Tinatin Tkemaladze, Omar Abdul‐Rahman, Drew Cratsenberg, Giulia Pascolini, Giovanni Di Zenzo, Daniele Castiglia, Emily Black, Camerun Washington, Lauren Chad, Cynthia Curry, Miguel Del Campo, Nicole Fleischer, Lynne M. Bird, Anna C. E. Hurst   +15 more
wiley   +1 more source

Explicable prioritization of genetic variants by integration of rule-based and machine learning algorithms for diagnosis of rare Mendelian disorders

Human Genomics
Background In the process of finding the causative variant of rare diseases, accurate assessment and prioritization of genetic variants is essential. Previous variant prioritization tools mainly depend on the in-silico prediction of the pathogenicity of ...
Ho Heon Kim, Dong-Wook Kim, Junwoo Woo, Kyoungyeul Lee   +3 more
doaj   +1 more source

Genetics of Response to ECT, TMS, Ketamine and Esketamine

American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.
ABSTRACT Treatment‐resistant mood disorders are often managed with intensive interventions that include electroconvulsive therapy (ECT), transcranial magnetic stimulation (TMS), ketamine, and esketamine, but the role of genetics in clinical response to those interventions is yet to be clearly determined.
Clio E. Franklin, Murat Altinay, Kala Bailey, Mahendra T. Bhati, Brent R. Carr, Susan K. Conroy, Khurshid Khurshid, William M. McDonald, Brian J. Mickey, James W. Murrough, Sean M. Nestor, Thomas Nickl‐Jockschat, Irving M. Reti, Gerard Sanacora, Nicholas T. Trapp, Biju Viswanath, Jesse H. Wright, Peter P. Zandi, James B. Potash   +18 more
wiley   +1 more source