AIMC Topic: Humans

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Reconstructing 3D chromosome structures from single-cell Hi-C data with SO(3)-equivariant graph neural networks.

NAR genomics and bioinformatics
The spatial conformation of chromosomes and genomes of single cells is relevant to cellular function and useful for elucidating the mechanism underlying gene expression and genome methylation. The chromosomal contacts (i.e. chromosomal regions in spa...

Deep learning-based analysis of gross features for ovarian epithelial tumors classification: A tool to assist pathologists for frozen section sampling.

Human pathology
Computational pathology has primarily focused on analyzing tissue slides, neglecting the valuable information contained in gross images. To bridge this gap, we proposed a novel approach leveraging the Swin Transformer architecture to develop a Swin-T...

The current state of forensic imaging - perspectives.

International journal of legal medicine
This fourth part of the review of the current state of forensic imaging describes the future potential influence of artificial intelligence in forensic imaging. In addition to this important point, training in forensic imaging is discussed in detail,...

Generative Artificial Intelligence (AI) in Chronic Dermatophytosis Patient Counseling: A Viable Alternative?

International journal of dermatology
Dermatophytosis pose a significant burden on patients leading to recurrence and decreased quality of life owing to inadequate patient education and non-compliance to the treatment. There is a potential role of generative Artificial Intelligence (AI) ...

Artificial intelligence for abdominopelvic trauma imaging: trends, gaps, and future directions.

Abdominal radiology (New York)
Abdominopelvic trauma is a major cause of morbidity and mortality, typically resulting from high-energy mechanisms such as motor vehicle collisions and penetrating injuries. Admission abdominopelvic trauma CT, performed either selectively or as part ...

Ovarian masses suggested for MRI examination: assessment of deep learning models based on non-contrast-enhanced MRI sequences for predicting malignancy.

Abdominal radiology (New York)
PURPOSE: We aims to assessed and compare four deep learning(DL) models using non-contrast-enhanced magnetic resonance imaging(MRI) to differentiate benign from malignant ovarian tumors, considering diagnostic efficacy and associated development costs...

PCANN Program for Structure-Based Prediction of Protein-Protein Binding Affinity: Comparison With Other Neural-Network Predictors.

Proteins
In this communication, we introduce a new structure-based affinity predictor for protein-protein complexes. This predictor, dubbed PCANN (Protein Complex Affinity by Neural Network), uses the ESM-2 language model to encode the information about prote...

Evaluation methods of pressure injury stages: A systematic review and meta-analysis.

Journal of tissue viability
BACKGROUND: Pressure injury is prevalent in clinical settings and demands precise staging for optimal care. Subjectivity and imprecision in traditional visual assessments have sparked the creation of advanced technology-based evaluation tools.