Psychiatry

Schizophrenia

Latest AI and machine learning research in schizophrenia for healthcare professionals.

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Advancing Creative Physical Intelligence in Large Multimodal Models

Large multimodal models (LMMs) have rapidly advanced in perception and reasoning; however, it remain...

Towards Reliable Fetal Ultrasound Interpretation with Multi-Agent Collaboration

Automated fetal ultrasound interpretation requires a workflow from visual perception, including plan...

Predicting Substance Use and Psychotic-Like Experiences in Adolescents

Adolescence is a critical developmental window for the emergence of substance use and psychosis-spec...

Riemannian geometry meets fMRI: the advantages of modeling correlation manifolds and eigenvector subspaces

Correlation matrices are fundamental summaries of functional brain networks, yet standard analyses o...

De novo designed cyclic MC4R peptide agonist reduces food intake in mice

Deep learning-based structure prediction enables the design of peptide ligands without relying on na...

ToxCastLite: A portable semantic evidence graph linking in vitro bioactivity, in vivo toxicity, and exposure-use context

Motivation: The ToxCast database is a valuable resource for computational toxicology and new approac...

Memisis: Orchestrating and Evaluating Synthetic Data for Tabular Health Datasets

Synthetic data is widely used in healthcare to create datasets that are similar to original data but...

When Looking Is Not Enough: Visual Attention Structure Reveals Hallucination in MLLMs

Multimodal large language models (MLLMs) have become a key interface for visual reasoning and ground...

Allegory of the Cave: Measurement-Grounded Vision-Language Learning

Vision-language models typically reason over post-ISP RGB images, although RGB rendering can clip, s...

CAWI: Copula-Aligned Weight Initialization for Randomized Neural Networks

Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing rando...

CRAFT: Clinical Reward-Aligned Finetuning for Medical Image Synthesis

Foundation diffusion models can generate photorealistic natural images, but adapting them to medical...

Med-StepBench: A Hierarchical Reasoning Framework for Evaluating Hallucinations in Medical Vision-Language Models

Large vision-language models (VLMs) demonstrate strong performance in medical image understanding, b...

EchoPrune: Interpreting Redundancy as Temporal Echoes for Efficient VideoLLMs

Long-form video understanding remains challenging for Video Large Language Models (VideoLLMs), as th...

Claim-Level Transparency Analysis of LLM-Generated Diagnostic Reports: A Metabolic and Endocrine Biomarker Study

Large language models are increasingly deployed in clinical decision-support contexts, yet systemati...

Fast and Ultra-Capable Protein Design: Advancing the Frontier Through Atomistic SE(3)-Equivariance with Genie 3

Despite the breakneck pace of progress in protein design methodology, frontier problems remain chall...

MK-ResRecon: Multi-Kernel Residual Framework for Texture-Aware 3D MRI Refinement from Sparse 2D Slices

Magnetic Resonance Imaging (MRI) acquisition remains a time-intensive and patient-straining process,...

FluxFlow: Conservative Flow-Matching for Astronomical Image Super-Resolution

Ground-to-space astronomical super-resolution requires recovering space-quality images from ground-b...

Online Self-Calibration Against Hallucination in Vision-Language Models

Large Vision-Language Models (LVLMs) often suffer from hallucinations, generating descriptions that ...

Instruction-Evidence Contrastive Dual-Stream Decoding for Grounded Vision-Language Reasoning

Vision-Language Models (VLMs) exhibit strong performance in instruction following and open-ended vis...

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