Latest AI and machine learning research in schizophrenia for healthcare professionals.
Visual planning, by offering a sequence of intermediate visual subgoals to a goal-conditioned low-...
The Cancer Genome Atlas (TCGA) has enabled novel discoveries and served as a large-scale reference...
Despite significant advancements in multimodal reasoning tasks, existing Large Vision-Language Mod...
In the age of social media, the rapid spread of misinformation and rumors has led to the emergence...
Vision-Language Models (VLMs) are becoming increasingly popular in the medical domain, bridging th...
The scarcity of high-quality multimodal biomedical data limits the ability to effectively fine-tune ...
BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which di...
BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex a...
BACKGROUND: Cognitive deficits are a central feature of schizophrenia for which there are not any es...
Retrieval-Augmented Generation (RAG) systems have gained widespread adoption by application builde...
Hallucinations in vision-language models (VLMs) hinder reliability and real-world applicability, u...
Zero-shot learning (ZSL) aims to recognize unseen classes by aligning images with intermediate cla...
The collaborative paradigm of large and small language models (LMs) effectively balances performan...
The acquisition of information-rich images within a limited time budget is crucial in medical imag...
Accurate extraction of key information from 2D engineering drawings is crucial for high-precision ...
Hallucinations in large language models (LLMs) present a growing challenge across real-world appli...
IMPORTANCE: The diagnosis of schizophrenia and bipolar disorder is often delayed several years despi...
Medical Large Multi-modal Models (LMMs) have demonstrated remarkable capabilities in medical data ...
Mental and cognitive representations are believed to reside on low-dimensional, non-linear manifol...
Blind harmonization has emerged as a promising technique for MR image harmonization to achieve sca...
With the widespread application of large language models (LLMs), the issue of generating non-exist...