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Bioterrorism

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

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Assessing the Readiness of European Healthcare Institutions for EU AI Act Compliance.

The European Union's Artificial Intelligence Act (EU AI Act) proposes a comprehensive regulatory fra...

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting.

Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of s...

Scaling up drug combination surface prediction.

Drug combinations are required to treat advanced cancers and other complex diseases. Compared with m...

AI-driven health analysis for emerging respiratory diseases: A case study of Yemen patients using COVID-19 data.

In low-income and resource-limited countries, distinguishing COVID-19 from other respiratory disease...

Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks.

Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspi...

Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer.

IMPORTANCE: Only a small fraction of patients with advanced non-small cell lung cancer (NSCLC) respo...

Individualized multi-treatment response curves estimation using RBF-net with shared neurons.

Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific in...

: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models.

Computer vision methods offer great potential for rapid image-based identification of medically impo...

Comparative analysis of multi-zone peritumoral radiomics in breast cancer for predicting NAC response using ABVS-based deep learning models.

BACKGROUND: Peritumoral characteristics demonstrate significant predictive value for neoadjuvant che...

Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning.

Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder. The inflammatory r...

Machine Learning Radiomics for Predicting Response to MR-Guided Radiotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Cohort Study.

BACKGROUND: This study was conducted to assess the efficacy and safety of magnetic resonance (MR)-gu...

A conceptual and computational framework for modeling the complex, adaptive dynamics of epidemics: The case of the SARS-CoV-2 pandemic in Mexico.

In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pan...

Artificial intelligence can help individualize Wilms tumor treatment by predicting tumor response to preoperative chemotherapy.

PURPOSE: To create a computer-aided prediction (CAP) system to predict Wilms tumor (WT) responsivene...

Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.

Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-...

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