Hematology

Hemophilia

Latest AI and machine learning research in hemophilia for healthcare professionals.

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Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.

Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of t...

Integrated transcriptomic and functional modeling reveals AKT and mTOR synergy in colorectal cancer.

Colorectal cancer (CRC) treatment remains challenging due to genetic heterogeneity and resistance me...

Longitudinal single-cell RNA model aids prediction of EGFR-TKI resistance.

Resistance is inevitable and a major challenge in treating Lung adenocarcinoma (LUAD) patients with ...

An integrated approach for novel PTP1B inhibitor screening: combining machine learning models, molecular docking, molecular and dynamics simulations.

Diabetes mellitus, particularly type 2 diabetes (T2DM), is a major global health challenge character...

Development of a machine learning-based predictive model for venous thromboembolism risk assessment in orthopaedic patients with routine prophylaxis.

Despite the use of conventional preventive measures, the long-term risk of the development of venous...

Transformative potential of artificial intelligence in US CDC HIV interventions: balancing innovation with health privacy.

Artificial intelligence (AI) holds significant potential to transform HIV prevention and treatment t...

AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches.

The increasing global incidence of cancer emphasizes the vital role of machine learning algorithms a...

Artificial intelligence-driven discovery of YH395A: A novel TGFβR1 inhibitor with potent anti-tumor activity against triple-negative breast cancer.

Characterized by high malignancy and limited treatment efficacy, triple-negative breast cancer (TNBC...

Machine learning-based QSAR and structure-based virtual screening guided discovery of novel mIDH1 inhibitors from natural products.

Mutations in isocitrate dehydrogenase 1 (IDH1) have been widely observed in various tumors, such as ...

Combining the NanaPPI Toolbox and AI-Driven Virtual Inhibitor Screening for the p53-MDM2 Interaction.

High-throughput screening for inhibitors of protein-protein interactions (PPIs) provides vital infor...

A computational study of cardiac glycosides from Vernonia amygdalina as PI3K inhibitors for targeting HER2 positive breast cancer.

The PI3K/Akt pathway plays a crucial role in regulating a broad network of proteins involved in the ...

Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis.

This study developed an immune-related long non-coding RNAs (lncRNAs)-based prognostic signature by ...

Can ChatGPT Provide Patient-Friendly and Reliable Information on Cervical Cancer Screening? A Study of ChatGPT-Generated Information in Polish.

BACKGROUND Cervical cancer (CC) mortality remains a global health problem, and women's awareness of ...

Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils.

The integration of Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs...

Deep learning-based dipeptidyl peptidase IV inhibitor screening, experimental validation, and GaMD/LiGaMD analysis.

BACKGROUND: Dipeptidyl peptidase-4 (DPP4) is considered a crucial enzyme in type 2 diabetes (T2D) tr...

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