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Devices and Vaccines

Latest AI and machine learning research in devices and vaccines for healthcare professionals.

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Showing 43-63 of 3,914 articles
Artificial Intelligence for Low-Dose CT Lung Cancer Screening: Comparison of Utilization Scenarios.

. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examina...

MoTe synaptic transistor and its application to physical reservoir computing.

In this study, we systematically analyzed the synaptic properties of an MoTe-based transistor and pr...

Development of an explainable machine learning model for predicting device-related pressure injuries in clinical settings.

BACKGROUND: Device-related pressure injury (DRPI) is a prevalent and severe problem for patients usi...

Prediction and characterisation of the human B cell response to a heterologous two-dose Ebola vaccine.

Ebola virus disease (EVD) outbreaks are increasing, posing significant threats to affected communiti...

Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.

Neoantigens, which are tumor-specific peptides generated by malignant cells, can be presented to T c...

Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model.

Intravenous immunoglobulin (IVIG) has been established as the first-line therapy for Kawasaki diseas...

Machine learning approaches to dissect hybrid and vaccine-induced immunity.

BACKGROUND: The spread of SARS-CoV-2 Omicron variant and its subvariants, highly transmissible but r...

Automatic Identification of Dental Implant Brands with Deep Learning Algorithms.

OBJECTIVES: To reduce the problems arising from the inability to identify dental implant brands, thi...

Predicting SARS-CoV-2-specific CD4 and CD8 T-cell responses elicited by inactivated vaccines in healthy adults using machine learning models.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highl...

Organic dual-channel transistors for reconfigurable signal modulation and anti-counterfeiting.

The development of integrated circuits and artificial intelligence demands electronic devices with v...

Enhancing diabetes risk prediction through focal active learning and machine learning models.

To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based o...

Mechanobiology-guided machine learning models for predicting long bone fracture healing across diverse scenarios.

BACKGROUND: Fracture healing is a complex, time-dependent process governed by biological and mechani...

Unraveling Stochastic Dynamics and Switching Mechanism in Ag Network-Based Neuromorphic Device by Impedance Spectroscopy.

Neuromorphic devices are leading advancements in brain-inspired computing. The present study employs...

Potential Time and Recall Benefits for Adaptive AI-Based Breast Cancer MRI Screening.

BACKGROUND: Abbreviated breast MRI protocols are advocated for breast screening as they limit acquis...

Air-ground collaborative multi-source orbital integrated detection system: Combining 3D imaging and intrusion recognition.

With the rapid expansion of railway networks globally, ensuring rail infrastructure safety through e...

A systematic review of machine learning approaches in cochlear implant outcomes.

Cochlear implants (CIs) have transformed the lives of over one million individuals with hearing impa...

[Regulatory classification of AI-enabled products for medical use on the basis of the EU AI Act and MDR/IVDR].

The use of artificial intelligence (AI) in healthcare offers great potential but also presents regul...

Laterally Gated CuInPS Ferroelectric Field Effect Transistors for Neuromorphic Computing.

With the rapid development of artificial intelligence (AI) technologies, the demand for data storage...

Machine learning algorithms for prediction of cerebrospinal fluid leakage after posterior surgery for thoracic ossification of the ligamentum flavum.

To develop and validate a machine-learning (ML) model that pre-operatively predicts cerebrospinal-fl...

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