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An optimized support vector machine for lung cancer classification system.
Front Oncol
December 2024
Honorary Research Associate, Department of Operations and Quality Management, Durban University of Technology, Durban, South Africa.
Introduction: Lung cancer is one of the main causes of the rising death rate among the expanding population. For patients with lung cancer to have a higher chance of survival and fewer deaths, early categorization is essential. The goal of thisresearch is to enhance machine learning to increase the precision and quality of lung cancer classification.
View Article and Find Full Text PDFAccuracy of MRI R2* Mapping in Diagnosis of Liver Iron Concentration: A Meta-Analysis.
J Magn Reson Imaging
January 2025
Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
While current guidelines recommend R2* method as the first-line method for liver iron concentration (LIC) measurement, its diagnostic accuracy is debatable. A prior meta-analysis suggested limited accuracy of R2* method for identifying patients with iron overload. However, substantial advances in R2* method over the past decade may have improved its diagnostic performance.
View Article and Find Full Text PDFThe relationship between electric field strength induced by electroconvulsive therapy and cognitive and antidepressant outcomes.
Neuropsychopharmacology
January 2025
Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands.
Electroconvulsive therapy (ECT) is an effective treatment for depression but is often associated with cognitive side effects. In patients, ECT-induced electric field (E-field) strength across brain regions varies significantly due to anatomical differences, which may explain individual differences in cognitive side effects. We examined the relationship between regional E-field strength and change in verbal fluency score (i.
View Article and Find Full Text PDFCardiac arrhythmia assessment with patch electrocardiogram versus insertable cardiac monitor: a cohort study in endurance athletes with atrial fibrillation.
BMJ Open
January 2025
Department of Medical Research Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway
Objectives: The objective of this study was to assess the quality of ECG recordings and the concordance between the automatic detection of cardiac arrhythmia episodes by a patch ECG and an insertable cardiac monitor.
Design: Prospective cohort study.
Setting And Participants: Endurance athletes diagnosed with paroxysmal atrial fibrillation (AF) and no other relevant comorbidities participating in a randomised controlled trial on the effects of training adaption.
Evaluating the pathological and clinical implications of errors made by an artificial intelligence colon biopsy screening tool.
BMJ Open Gastroenterol
January 2025
Histopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.
Objective: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an AI algorithm that can effectively classify colonic biopsies into normal versus abnormal categories, designed to automatically report normal cases. We performed a retrospective pathological and clinical review of the errors made by IGUANA.
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