Results 141 to 150 of about 28,464 (292)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

open access: yesAdvanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu   +16 more
wiley   +1 more source

The Role of Demoghraphy in Moderation the Influence of Physician's Non Verbal Communication to Patient's Satisfaction

open access: yes, 2015
Effective non verbal communication affects patient's satisfaction as well as optimal level of patient's healthiness. This is primarily due to asymmetry information between doctor and patient since in most cases patients heavily rely on non verbal ...
A Pasinringi, Syahrir   +2 more
core  

Paternal Caffeine Exposure Programs Offspring Stress Vulnerability via Sperm Dlk1‐Dio3 Imprinting‐Directed Remodeling of a Novel Neural Circuit

open access: yesAdvanced Science, EarlyView.
The study elucidates that paternal preconception stress can drive offspring hyperresponsivity of the stress system via hypomethylation of a specific DNA region in sperm. This key link is confirmed in a cohort of prospective fathers: the epigenetic alteration is associated with elevated stress hormone levels.
Mengxi Lu   +10 more
wiley   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

open access: yesAdvanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu   +8 more
wiley   +1 more source

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