Intrinsically disordered proteins and regions (IDRs) lack stable 3D structures, posing challenges for interaction prediction. We present SpatPPI, a geometric deep learning model tailored for IDPPI prediction. SpatPPI leverages structural cues from fo...
PURPOSE: To synthesize evidence on deep learning applications for diagnosing central serous chorioretinopathy (CSCR), a macular disorder associated with vision loss, this systematic review categorized studies by diagnostic task and imaging modality. ...
OBJECTIVE: Accurate cancer risk prediction is hindered by complex, multi-layered immune interactions, and traditional tissue biopsies are invasive and lack scalability for large-scale or repeated assessments. Peripheral blood offers a minimally invas...
Early diagnosis of skin cancer remains a pressing challenge in dermatological and oncological practice. AI-driven learning models have emerged as powerful tools for automating the classification of skin lesions by using dermoscopic images. This study...
This study aims to forecast the spread of acute diarrhoea and dengue diseases in India by conducting a comparative analysis of statistical, mathematical (compartmental), and deep learning time series models. Utilizing weekly reported cases and fatali...
Co-folding models represent a major innovation in deep-learning-based protein-ligand structure prediction. The recent publications of RoseTTAFold All-Atom, AlphaFold3, and others have shown high-quality results on predicting the structures of protein...
Brain tumour identification, segmentation cataloguing from MRI images is most thought-provoking and is a very much essential for many medical image analysis applications. Every brain imaging modality provides information about various parts of the tu...
Industrial wood production plays a vital role in the economies of many countries by supplying raw materials for a wide range of sectors, including construction, paper, and pulp industries. However, the industry is increasingly challenged by the detri...
Journal of computer-aided molecular design
Oct 6, 2025
Protein pockets, or small cavities on the protein surface, are critical sites for enzymatic catalysis, molecular recognition, and drug binding. Accurately identifying these pockets is crucial for understanding protein function and designing therapeut...
Predicting short-term passenger flow in urban rail transit is crucial for intelligent and real-time management of urban rail systems. This study utilizes deep learning techniques and multi-source big data to develop an enhanced spatial-temporal long ...
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