BACKGROUND: Cone-beam computed tomography (CBCT) is a crucial daily imaging modality in image-guided and adaptive radiotherapy. However, the use of ionizing radiation in CBCT imaging increases the risk of secondary cancers, which is particularly conc...
The COVID-19 pandemic has emerged as a global health crisis, impacting millions worldwide. Although chest computed tomography (CT) scan images are pivotal in diagnosing COVID-19, their manual interpretation by radiologists is time-consuming and poten...
Heart diseases remain one of the leading causes of death worldwide. As a result, early and accurate diagnostics have become an urgent need for treatment and management. Most of the conventional methods adopted tend to have major drawbacks: the issues...
This study systematically reviews CNN-based medical image classification methods. We surveyed 149 of the latest and most important papers published to date and conducted an in-depth analysis of the methods used therein. Based on the selected literatu...
OBJECTIVE: This study aimed to outline a machine learning model to assess the effectiveness of vaccination in COVID-19 confirmed cases and fatalities. The proposed model was evaluated using external validation to ensure optimal protection of vaccinat...
Journal of applied clinical medical physics
Dec 3, 2024
BACKGROUND: Four-dimensional CT is increasingly used for functional cardiac imaging, including prognosis for conditions such as heart failure and post myocardial infarction. However, radiation dose from an acquisition spanning the full cardiac cycle ...
Cranial sex estimation often relies on visual assessments made by a forensic anthropologist following published standards. However, these methods are prone to human bias and may be less accurate when applied to populations other than those for which ...
Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) because they offer non-invasive and easily accessible tools. By using advanced data analysis, these methods improve early detection and diagnosis, which i...
This study introduces a novel method for predicting the Big Five personality traits through the analysis of speech samples, advancing the field of computational personality assessment. We collected data from 2045 participants who completed a self-rep...
The array of complex and evolving patient data has limited clinical decision making in the emergency department (ED). This study introduces an advanced deep learning algorithm designed to enhance real-time prediction accuracy for integration into a n...
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