A clear understanding of the fundamentals of ML improves the quality of explanations in interviews.Practical knowledge of Python libraries can be ...

Abstract: Here, we propose a hybrid Deep Learning (DL) framework consisting of a Denoising Autoencoder (DAE), Convolutional Neural Network (CNN), Bidirectional LSTM (BiLSTM), and a custom Attention ...

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Nearly six years later, checks from a $2.67 billion settlement fund related to Blue Cross Blue Shield health insurance will be distributed to affected subscribers in 2026. In October 2020, Blue Cross ...

Prognostic assessment in acute-on-chronic liver failure (ACLF), particularly in HBV-endemic regions, remains challenging due to the limited accuracy of conventional models. We aimed to develop and ...

2 State Key Laboratory of Trauma and Chemical Poisoning, Chongqing, China 3 Chongqing Key Laboratory of Hematology and Microenvironment, Chongqing, China Participants This study analysed 471 newly ...

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...

Traumatic brain injury (TBI) often causes visual symptoms that hinder rehabilitation. The Brain Injury Vision Symptom Survey (BIVSS) is an established 28-item questionnaire for TBI-related visual ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...