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Bioterrorism

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

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Showing 946-966 of 1,540 articles
Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach.

In this work we present a three-stage Machine Learning strategy to country-level risk classification...

A novel approach for personalized response model: deep learning with individual dropout feature ranking.

Deep learning is the fastest growing field in artificial intelligence and has led to many transforma...

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the stagge...

Ensemble transfer learning for the prediction of anti-cancer drug response.

Transfer learning, which transfers patterns learned on a source dataset to a related target dataset ...

Digital Twin Coaching for Physical Activities: A Survey.

Digital Twin technology has been rising in popularity thanks to the popularity of machine learning i...

Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design.

Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designi...

Serum midkine levels for the diagnosis and assessment of response to interventional therapy in patients with hepatocellular carcinoma.

OBJECTIVE: To explore the clinical significance of serum midkine (MDK) levels for the diagnosis of h...

Machine learning and individual variability in electric field characteristics predict tDCS treatment response.

BACKGROUND: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic t...

Customised Selection of the Haptic Design in C-Loop Intraocular Lenses Based on Deep Learning.

In order to increase the probability of having a successful cataract post-surgery, the customisation...

Peginterferon and Entecavir Combination Therapy Improves Outcome of Non-Early Response Hepatitis B e Antigen-Positive Patients.

BACKGROUND: The efficacy of nucleot(s)ide analogs (NAs) and pegylated interferon (PegIFN) combinatio...

Leveraging TCGA gene expression data to build predictive models for cancer drug response.

BACKGROUND: Machine learning has been utilized to predict cancer drug response from multi-omics data...

Using Item Response Theory for Explainable Machine Learning in Predicting Mortality in the Intensive Care Unit: Case-Based Approach.

BACKGROUND: Supervised machine learning (ML) is being featured in the health care literature with st...

A Demonstration of Machine Learning in Detecting Frequency Following Responses in American Neonates.

In this study, we sought to evaluate the efficiencies of multiple machine learning algorithms in det...

Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma.

BACKGROUND: Deep learning is promising to predict treatment response. We aimed to evaluate and valid...

Modeling adult skeletal stem cell response to laser-machined topographies through deep learning.

The response of adult human bone marrow stromal stem cells to surface topographies generated through...

Machine learning predicts stem cell transplant response in severe scleroderma.

OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical b...

Optimization and validation for quantification for allulose of jelly candies using response surface methodology.

A simple, rapid and reliable extraction method for allulose content in jelly were optimized using re...

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