Latest AI and machine learning research in schizophrenia for healthcare professionals.
Vision-language models (VLMs) have demonstrated remarkable potential in integrating visual and linguistic information, but their performance is often constrained by the need for extensive, high-quality image-text training data. Curation of these image-text pairs is both time-consuming and computationally expensive. To address this challenge, we introduce SVP (Sampling-based Visual Projection), a...
In current medical practice, patients undergoing depression treatment must wait four to six weeks before a clinician can assess medication response due to the delayed noticeable effects of antidepressants. Identification of a treatment response at any earlier stage is of great importance, since it can reduce the emotional and economic burden connected with the treatment. We approach the predicti...
Retrieval-augmented generation (RAG) improves large language models (LLMs) by using external knowledge to guide response generation, reducing halluc...
Complex visual reasoning remains a key challenge today. Typically, the challenge is tackled using methodologies such as Chain of Thought (COT) and v...
The chapter discusses the foundational impact of modern generative AI models on information access (IA) systems. In contrast to traditional AI, the ...
Large language models and vision transformers have demonstrated impressive zero-shot capabilities, enabling significant transferability in downstrea...
As the impact of global climate change intensifies, corporate carbon emissions have become a focal point of global attention. In response to issues ...
This study presents a software pipeline that leverages LLMs to apply knowledge stored in natural language (such as in pharmacological texts) and ontol...
Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emer...
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 (OB), the first central relay of the olfactory pathway, plays a critical role in odor perception and exhibits remarkable structural...
Mesocorticolimbic dopamine projections are crucial for value learning, motivational control, and cognitive functions, but their precise neurocomputati...
Predictive processing theories propose that the brain supervises itself, to build an internal model of its environment. This internal model emerges by...
Artificial intelligence (AI) is revolutionizing protein engineering, yet its practical application is often hindered by a fragmented toolchain and the...
The human claustrum is a bilateral, thin, irregularly shaped gray matter structure located between the striatum and insula. While previous research de...
Identifying promising therapeutic targets from thousands of genes in transcriptomic studies remains a major bottleneck in biomedical research. While l...
Functional MRI enables non-invasive mapping of brain connectivity, yet its clinical translation remains hindered by uncontrolled state-dependent varia...
Neuromodulation is a complex process in which chemical substances modulate brain activity, allowing its rich repertoire of behaviors. Among these subs...
Schizophrenia (ScZ) is a growing global health concern that affects millions of people and puts severe pressure on healthcare systems. Early detection...
Formal thought disorder (FTD) is a core symptom of schizophrenia, yet the neural network mechanisms underlying this phenotype remain poorly understood...