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Bioterrorism

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

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Showing 232-252 of 1,532 articles
Post-Bariatric Hypoglycemia After Gastric Bypass: Clinical Characteristics, Risk Factors, and Future Directions-A Response to Grover et al.

BACKGROUND: Post-bariatric hypoglycemia (PBH) after Roux-en-Y gastric bypass (RYGB) is a complex com...

Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.

A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repu...

Predicting inflammatory response of biomimetic nanofibre scaffolds for tissue regeneration using machine learning and graph theory.

Tissue regeneration after a wound occurs through three main overlapping and interrelated stages name...

DRExplainer: Quantifiable interpretability in drug response prediction with directed graph convolutional network.

Predicting the response of a cancer cell line to a therapeutic drug is pivotal for personalized medi...

Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.

Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from...

Pharmacogenomics and response to lithium in bipolar disorder.

AIMS: The present review explores the existing evidence on pharmacogenomic tests for prediction of l...

Identification of Biomarkers for Response to Interferon in Chronic Hepatitis B Based on Bioinformatics Analysis and Machine Learning.

Interferon (IFN) is a pivotal agent against hepatitis B virus (HBV) in clinic, but there is a lack o...

[MP-MRI in the evaluation of non-operative treatment response, for residual and recurrent tumor detection in head and neck cancer].

As non-surgical therapies gain acceptance in head and neck tumors, the importance of imaging has inc...

Investigation of Trajectory Tracking Control in Hip Joints of Lower-Limb Exoskeletons Using SSA-Fuzzy PID Optimization.

The application of lower-limb exoskeleton robots in rehabilitation is becoming more prevalent, where...

Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study.

PURPOSE: To utilize a convolutional neural network (CNN) to predict the response of treatment-naïve ...

A series of natural language processing for predicting tumor response evaluation and survival curve from electronic health records.

BACKGROUND: The clinical information housed within unstructured electronic health records (EHRs) has...

A deep-learning model for predicting tyrosine kinase inhibitor response from histology in gastrointestinal stromal tumor.

Over 90% of gastrointestinal stromal tumors (GISTs) harbor mutations in KIT or PDGFRA that can predi...

Combining machine learning with external validation to explore necroptosis and immune response in moyamoya disease.

Moyamoya disease (MMD) is a rare chronic vascular disease leads to cognitive impairment and stroke w...

A systematic review of structural neuroimaging markers of psychotherapeutic and pharmacological treatment for obsessive-compulsive disorder.

Identifying individual difference factors associated with treatment response and putative mechanisms...

Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.

OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular...

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