AIMC Topic: Humans

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The CT-based deep learning model outperforms traditional anatomical classification models in preoperatively predicting complications and risk grade in partial nephrectomy.

World journal of urology
PURPOSE: A deep learning model integrating CT radiomics and clinical features was developed to predict perioperative complications and risk grade in patients undergoing partial nephrectomy, and was compared to traditional anatomical classification mo...

Artificial intelligence-driven epigenetic CRISPR therapeutics: a structured multi-domain meta-analysis of therapeutic efficacy, off-target prediction, and gRNA optimization.

Functional & integrative genomics
CRISPR-based epigenetic editing enables reversible regulation of gene expression without permanent DNA modification. The integration of artificial intelligence (AI) enhances guide RNA (gRNA) design, off-target prediction, and delivery optimization. W...

Hybrid Sampling and Ensemble Learning for Food Safety Sampling Inspection Classification.

Journal of food protection
Food safety sampling inspection is critical for risk prevention in complex supply chains. However, extreme class imbalance, where unqualified samples are significantly outnumbered by qualified ones, biases machine learning (ML) models to prioritize m...

Decoding herbal medicine: AI-powered omics and network pharmacology.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: As global health challenges continue to evolve, herbal medicines (HMs) have garnered significant scientific interest as a valuable resource for treating complex diseases. However, the chemical complexity of HMs presents considerable chall...

Role of artificial intelligence in medical image analysis.

Chinese medical journal
With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT ...

Deep Learning in neuroimaging for neurodegenerative diseases: State-of-the art, Challenges, and Opportunities.

Journal of the neurological sciences
Neuroimaging is commonly used to diagnose neurodegenerative diseases (NDDs), providing crucial insights into brain changes before clinical symptoms manifest. Deep learning (DL) for neuroimaging can improve early diagnosis and disease monitoring. Clin...

Identification of key diagnostic and prognostic biomarkers for aortic valve stenosis with coronary artery disease through immunological profiling integrating proteomics, single-cell sequencing, and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Aortic valve stenosis with coronary artery disease (AS-CAD) represents a common yet complex cardiovascular comorbidity, characterized by multifactorial pathogenesis and a lack of specific serum biomarkers. These limitations hinder early d...

Etiology-Agnostic Diagnosis of Early Myocardial Ischemia via AI-Driven Label-Free Spectral Histopathology.

Analytical chemistry
Myocardial ischemia is a core pathological mechanism in diverse fatal diseases and can be triggered by multiple factors. Diagnosing early myocardial ischemia (EMI) caused by nontraditional factors (e.g., drugs or stress) remains challenging due to su...

Gemini SERS for Cross-Category Biomarker Detection and Early Warning of Sudden Cardiac Death in Acute Coronary Syndrome.

ACS nano
Simultaneous detection of metabolites and proteins─two chemically and functionally distinct classes of biomolecules─in complex biofluids remains a significant analytical hurdle, yet is critical for early and accurate disease diagnosis. These difficul...

Improving outbreak forecasts through model augmentation.

Proceedings of the National Academy of Sciences of the United States of America
Accurate forecasts of disease outbreaks are critical for effective public health responses, management of healthcare surge capacity, and communication of public risk. There are a growing number of powerful forecasting methods that fall into two broad...