AIMC Topic: Algorithms

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Study of AI algorithms on mpMRI and PHI for the diagnosis of clinically significant prostate cancer.

Urologic oncology
OBJECTIVE: To study the feasibility of multiple factors in improving the diagnostic accuracy of clinically significant prostate cancer (csPCa).

BindUP-Alpha: A Webserver for Predicting DNA-and RNA-binding Proteins based on Experimental and Computational Structural Models☆.

Journal of molecular biology
Structural data provides important information on the proteins' function. Recent development of advanced machine learning and artificial intelligence tools, such as AlphaFold, have led to an explosion of predicted protein structures. However, many of...

DeepMS: super-fast peptide identification using end-to-end deep learning method.

Journal of molecular biology
Mass spectrometry (MS) has emerged as a powerful omics analysis technique, particularly in proteomics, where the initial step involves identifying MS spectra as peptide sequences. However, this process often requires substantial computational resourc...

A cell-interacting and multi-correcting method for automatic circulating tumor cells detection.

Artificial intelligence in medicine
Sensitive detection of circulating tumor cells (CTCs) from peripheral blood can serve as an effective tool in the early diagnosis and prognosis of cancer. Many methods based on modern object detectors were proposed in recent years for automatic abnor...

An AI system for continuous knee osteoarthritis severity grading: An anomaly detection inspired approach with few labels.

Artificial intelligence in medicine
The diagnostic accuracy and subjectivity of existing Knee Osteoarthritis (OA) ordinal grading systems has been a subject of on-going debate and concern. Existing automated solutions are trained to emulate these imperfect systems, whilst also being re...

Symbolic and hybrid AI for brain tissue segmentation using spatial model checking.

Artificial intelligence in medicine
Segmentation of 3D medical images, and brain segmentation in particular, is an important topic in neuroimaging and in radiotherapy. Overcoming the current, time consuming, practise of manual delineation of brain tumours and providing an accurate, exp...

PhenoLinker: Phenotype-gene link prediction and explanation using heterogeneous graph neural networks.

Artificial intelligence in medicine
The association of a given human phenotype with a genetic variant remains a critical challenge in biomedical research. We present PhenoLinker, a novel graph-based system capable of associating a score to a phenotype-gene relationship by using heterog...

Deep learning model for malignancy prediction of TI-RADS 4 thyroid nodules with high-risk characteristics using multimodal ultrasound: A multicentre study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The automatic screening of thyroid nodules using computer-aided diagnosis holds great promise in reducing missed and misdiagnosed cases in clinical practice. However, most current research focuses on single-modal images and does not fully leverage th...

Taco-DDI: accurate prediction of drug-drug interaction events using graph transformer-based architecture and dynamic co-attention matrices.

Neural networks : the official journal of the International Neural Network Society
Drug-drug interactions (DDIs) are critical in pharmaceutical research, as adverse interactions can pose significant risks for patient treatment plans. Accurate prediction of DDI events risk levels can provide valuable guidance for designing safer and...

Overlapping community detection via Layer-Jaccard similarity incorporated nonnegative matrix factorization.

Neural networks : the official journal of the International Neural Network Society
As information modernization progresses, the connections between entities become more elaborate, forming more intricate networks. Consequently, the emphasis on community detection has transitioned from discerning disjoint communities towards the iden...