AIMC Topic: Sensitivity and Specificity
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Use of Artificial Intelligence Software to Detect Intracranial Aneurysms: A Comprehensive Stroke Center Experience.
World neurosurgery
May 10, 2024
OBJECTIVE: To evaluate variability in aneurysm detection and the potential of artificial intelligence (AI) software as a screening tool by comparing conventional computed tomography angiography (CTA) images (standard care) with AI software.
Machine learning-based bioimpedance assessment of knee osteoarthritis severity.
Biomedical physics & engineering express
May 10, 2024
This study proposes a multiclass model to classify the severity of knee osteoarthritis (KOA) using bioimpedance measurements. The experimental setup considered three types of measurements using eight electrodes: global impedance with adjacent pattern...
Deep learning-based detection of irreversible pulpitis in primary molars.
International journal of paediatric dentistry
May 9, 2024
BACKGROUND: Changes in healthy and inflamed pulp on periapical radiographs are traditionally so subtle that they may be imperceptible to human experts, limiting its potential use as an adjunct clinical diagnostic feature.
Artificial Intelligence in Dermatology: A Systematic Review of Its Applications in Melanoma and Keratinocyte Carcinoma Diagnosis.
Dermatologic surgery : official publication for American Society for Dermatologic Surgery [et al.]
May 9, 2024
BACKGROUND: Limited access to dermatologic care may pose an obstacle to the early detection and intervention of cutaneous malignancies. The role of artificial intelligence (AI) in skin cancer diagnosis may alleviate potential care gaps.
Artificial intelligence-based, semi-automated segmentation for the extraction of ultrasound-derived radiomics features in breast cancer: a prospective multicenter study.
La Radiologia medica
May 9, 2024
PURPOSE: To investigate the feasibility of an artificial intelligence (AI)-based semi-automated segmentation for the extraction of ultrasound (US)-derived radiomics features in the characterization of focal breast lesions (FBLs).
Improving sepsis classification performance with artificial intelligence algorithms: A comprehensive overview of healthcare applications.
Journal of critical care
May 8, 2024
PURPOSE: This study investigates the potential of machine learning (ML) algorithms in improving sepsis diagnosis and prediction, focusing on their relevance in healthcare decision-making. The primary objective is to contribute to healthcare decision-...
Clinically Applicable Pan-Origin Cancer Detection for Lymph Nodes via Artificial Intelligence-Based Pathology.
Pathobiology : journal of immunopathology, molecular and cellular biology
May 8, 2024
INTRODUCTION: Lymph node metastasis is one of the most common ways of tumour metastasis. The presence or absence of lymph node involvement influences the cancer's stage, therapy, and prognosis. The integration of artificial intelligence systems in th...
A radiograph-based deep learning model improves radiologists' performance for classification of histological types of primary bone tumors: A multicenter study.
European journal of radiology
May 7, 2024
PURPOSE: To develop a deep learning (DL) model for classifying histological types of primary bone tumors (PBTs) using radiographs and evaluate its clinical utility in assisting radiologists.
Deep Learning Diagnostic Classification of Cervical Images to Augment Colposcopic Impression.
Journal of lower genital tract disease
May 7, 2024
OBJECTIVE: A deep learning classifier that improves the accuracy of colposcopic impression.
A novel artificial intelligence-based endoscopic ultrasonography diagnostic system for diagnosing the invasion depth of early gastric cancer.
Journal of gastroenterology
May 7, 2024
BACKGROUND: We developed an artificial intelligence (AI)-based endoscopic ultrasonography (EUS) system for diagnosing the invasion depth of early gastric cancer (EGC), and we evaluated the performance of this system.
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