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Bioterrorism

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

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Modern technologies and solutions to enhance surveillance and response systems for emerging zoonotic diseases.

BACKGROUND: Zoonotic diseases originating in animals pose a significant threat to global public heal...

Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.

INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be...

Single-Cell Radiation Response Scoring with the Deep Learning Algorithm CeCILE 2.0.

External stressors, such as ionizing radiation, have massive effects on life, survival, and the abil...

Fungal and bacterial gut microbiota differ between colonization and infection.

The bacterial microbiota is well-recognized for its role in colonization and infection, while fung...

Deep learning-enabled breast cancer endocrine response determination from H&E staining based on ESR1 signaling activity.

Estrogen receptor (ER) positivity by immunohistochemistry has long been a main selection criterium f...

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening.

OBJECTIVES: Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) a...

Deep learning with fetal ECG recognition.

Independent component analysis (ICA) is widely used in the extraction of fetal ECG (FECG). However, ...

The leading global health challenges in the artificial intelligence era.

Millions of people's health is at risk because of several factors and multiple overlapping crises, a...

Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: To develop and validate a radiogenomics model integrating clinical data, r...

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning.

Here, we provide a new methodology for reducing false results and time delay of biosensors, which ar...

Development of yogurt fortified with four varieties of common bean () whey by using response surface methodology: a preliminary study.

UNLABELLED: In recent years, there has been a growing interest in developing novel foods with improv...

Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.

RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary res...

Triple-crises-induced food insecurity: systematic understanding and resilience building approaches in Africa.

The triple crises of the COVID-19 pandemic, conflict and climate change have severely impacted food ...

An intronic genetic variant of ZHX2 predicts response to pegylated interferon α therapy in HBeAg-positive chronic hepatitis B patients.

ZHX2 plays a crucial role in host immunity and modulates hepatitis B virus (HBV) replication. Howeve...

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