Psychiatry

Schizophrenia

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

3,231 articles
Stay Ahead - Weekly Schizophrenia research updates
Subscribe
Browse Categories
Showing 1061-1080 of 3,231 articles

Socratic Questioning: Learn to Self-guide Multimodal Reasoning in the Wild

Complex visual reasoning remains a key challenge today. Typically, the challenge is tackled using methodologies such as Chain of Thought (COT) and visual instruction tuning. However, how to organically combine these two methodologies for greater success remains unexplored. Also, issues like hallucinations and high training cost still need to be addressed. In this work, we devise an innovative mu...

Foundations of GenIR

The chapter discusses the foundational impact of modern generative AI models on information access (IA) systems. In contrast to traditional AI, the large-scale training and superior data modeling of generative AI models enable them to produce high-quality, human-like responses, which brings brand new opportunities for the development of IA paradigms. In this chapter, we identify and introduce tw...

EAGLE: Enhanced Visual Grounding Minimizes Hallucinations in Instructional Multimodal Models

Large language models and vision transformers have demonstrated impressive zero-shot capabilities, enabling significant transferability in downstrea...

CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System

As the impact of global climate change intensifies, corporate carbon emissions have become a focal point of global attention. In response to issues ...

Biological Database Mining for LLM-Driven Alzheimer’s Disease Drug Repurposing

This study presents a software pipeline that leverages LLMs to apply knowledge stored in natural language (such as in pharmacological texts) and ontol...

The Fengshu Large Model for Wugu Fengdeng: An Innovation Engine for Knowledge Integration in the Soybean Field

Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emer...

Fold-Conditioned De Novo Binder Design via AlphaFold2-Multimer Hallucination

De novo protein binder design has been revolutionized by deep learning methods, yet controlling binder topology remains a challenge. We introduce a fo...

The olfactory bulb reflects structural plasticity within a genetically stable olfactory network

The olfactory bulb (OB), the first central relay of the olfactory pathway, plays a critical role in odor perception and exhibits remarkable structural...

Mesocorticolimbic reinforcement learning of reward representation and value provides an integrated mechanistic account for schizophrenia

Mesocorticolimbic dopamine projections are crucial for value learning, motivational control, and cognitive functions, but their precise neurocomputati...

A genetic algorithm for self-supervised models of oscillatory neurodynamics

Predictive processing theories propose that the brain supervises itself, to build an internal model of its environment. This internal model emerges by...

PRIME: A Multi-Agent Environment for Orchestrating Dynamic Computational Workflows in Protein Engineerings

Artificial intelligence (AI) is revolutionizing protein engineering, yet its practical application is often hindered by a fragmented toolchain and the...

Claustrum volume in humans – lifespan trajectory and effect of age, hemisphere, and sex

The human claustrum is a bilateral, thin, irregularly shaped gray matter structure located between the striatum and insula. While previous research de...

Automating Candidate Gene Prioritization with Large Language Models: From Naive Scoring to Literature-Grounded Validation

Identifying promising therapeutic targets from thousands of genes in transcriptomic studies remains a major bottleneck in biomedical research. While l...

PI-FC: Pre-training Individual-specific Functional Connectome through State-invariant Contrastive Learning

Functional MRI enables non-invasive mapping of brain connectivity, yet its clinical translation remains hindered by uncontrolled state-dependent varia...

Next generation neural mass model with dopamine modulation mediated by D1-type receptors

Neuromodulation is a complex process in which chemical substances modulate brain activity, allowing its rich repertoire of behaviors. Among these subs...

Exploring brain lobe-specific insights in an explainable framework for EEG-based schizophrenia detection

Schizophrenia (ScZ) is a growing global health concern that affects millions of people and puts severe pressure on healthcare systems. Early detection...

Dynamic Meta-Networking Identifies Distinct Network Correlates of Positive and Negative Formal Thought Disorder in Schizophrenia

Formal thought disorder (FTD) is a core symptom of schizophrenia, yet the neural network mechanisms underlying this phenotype remain poorly understood...

Decision Voting Based Multiscale Convolutional Learning of Brain Networks With Explainability

The diagnosis of neurological disorders requires comprehensive frameworks that incorporate multimodal neuroimaging data while ensuring clinical interp...

HalluDesign: Protein Optimization and de novo Design via Iterative Structure Hallucination and Sequence design

Deep learning has revolutionized biomolecular modeling, enabling the prediction of diverse structures with atomic accuracy. However, leveraging the at...

Model-based EEG phenotyping uncovers distinct neurocomputational mechanisms underlying learning impairments across psychopathologies

Major depressive disorder (MDD), bipolar disorder (BP), and schizophrenia (SCZ) involve learning impairments with poorly understood mechanisms. Unders...

Browse Categories