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Bioterrorism

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

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High performance COVID-19 screening using machine learning.

Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an ...

Preparation and optimisation of solid lipid nanoparticles of rivaroxaban using artificial neural networks and response surface method.

AIMS: This study aimed to improve rivaroxaban delivery by optimising solid lipid nanoparticles (SLN)...

The use of machine learning for the prediction of response to follow-up in spine registries.

BACKGROUND: One of the main challenges in the maintenance of registries is to keep a high follow-up ...

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide l...

Explainable Machine Learning to Predict Treatment Response in Advanced Non-Small Cell Lung Cancer.

PURPOSE: Immune checkpoint inhibitors (ICIs) have demonstrated promise in the treatment of various c...

Drug molecular representations for drug response predictions: a comprehensive investigation via machine learning methods.

The integration of drug molecular representations into predictive models for Drug Response Predictio...

Drug discovery and mechanism prediction with explainable graph neural networks.

Apprehension of drug action mechanism is paramount for drug response prediction and precision medici...

Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatm...

Forecasting Pediatric Trauma Volumes: Insights From a Retrospective Study Using Machine Learning.

INTRODUCTION: Rising pediatric firearm-related fatalities in the United States strain Trauma Centers...

Radiologists' perceptions and readiness for integrating artificial intelligence in diagnostic imaging: A survey-based study.

Artificial intelligence (AI) is revolutionizing diagnostic imaging, enhancing precision, speed and e...

Fault diagnosis of nonlinear analog circuits using generalized frequency response function and LSSVM.

A fault diagnosis method of nonlinear analog circuits is proposed that combines the generalized freq...

Comparative evaluation of feature reduction methods for drug response prediction.

Personalized medicine aims to tailor medical treatments to individual patients, and predicting drug ...

A machine learning-based immune response signature to facilitate prognosis prediction in patients with endometrial cancer.

Endometrial cancer is the most prevalent form of gynecologic malignancy, with a significant surge in...

Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.

The response of the kidney after induction treatment is one of the determinants of prognosis in lupu...

Machine learning prediction model of the treatment response in schizophrenia reveals the importance of metabolic and subjective characteristics.

Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic a...

Will AI reshape or deform pharmacy education?

The integration of artificial intelligence (AI) into pharmacy education offers transformative opport...

Development of a short form of the Geriatric Depression Scale-30 based on item response theory and the RiskSLIM algorithm.

Recently, methods of quickly and accurately screening for geriatric depression have attracted substa...

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