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

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Showing 85-105 of 6,756 articles
Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods.

In complex geological environments, the morphology, orientation and distribution characteristics of ...

ML enhanced bioactivity prediction for angiotensin II receptor: A potential anti-hypertensive drug target.

The process of drug discovery is intricate, and encompasses a series of detailed phases of research,...

Using of aluminum (lignin /silica /fatty acids) hybrid filler in the fabrication of natural rubber conductive elastomers.

Green flexible conductive composites (FCCs) with high flexibility and foldability have potential use...

Harnessing AlphaFold to reveal hERG channel conformational state secrets.

To design safe, selective, and effective new therapies, there must be a deep understanding of the st...

Biomolecular Interaction Prediction in the Pre- and Post-AlphaFold Era: The 8th CAPRI Evaluation.

We report on the 8th CAPRI Evaluation period, capturing the assessment of CAPRI Rounds 47 to 55 (exc...

Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.

Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising app...

Self-Assembly MXene/PDA@Cotton Fabric Pressure Sensor Integrated with Deep Learning for Sign Language Recognition.

In recent years, smart textiles and flexible wearable products have garnered significant attention i...

Machine Learning for Genomic Profiling and Drug Discovery in Personalised Lung Cancer Therapeutics.

Lung cancer is a prevalent and lethal malignancy characterised by the uncontrolled growth of abnorma...

A Network-Driven Framework for Drug Response Precision Prediction of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a clonal malignancy of myeloid progenitor cells that demonstrates hi...

SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.

Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers...

EDRMM: enhancing drug recommendation via multi-granularity and multi-attribute representation.

BACKGROUND: Drug recommendation is a crucial application of artificial intelligence in medical pract...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of s...

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 for Low-Dose CT Lung Cancer Screening: Comparison of Utilization Scenarios.

. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examina...

Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey.

In recent years, generative deep learning has emerged as a transformative approach in drug design, p...

Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model.

Intravenous immunoglobulin (IVIG) has been established as the first-line therapy for Kawasaki diseas...

Δ-Machine Learning of Polarizability Tensors Using a Dipole Interaction Model.

As a fundamental response property, the molecular polarizability is responsible for a wide variety o...

MRDDA: a multi-relational graph neural network for drug-disease association prediction.

BACKGROUND: Drug repositioning offers a promising avenue for accelerating drug development and reduc...

Gesture recognition and response system for special education using computer vision and human-computer interaction technology.

Gesture recognition has emerged as a pivotal technology for enhancing human-computer interaction (HC...

Enhancing diabetes risk prediction through focal active learning and machine learning models.

To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based o...

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