BACKGROUND: Artificial intelligence (AI) has potential uses in healthcare including the detection of health conditions and prediction of health outcomes. Past systematic reviews had reviewed the accuracy of artificial neural networks (ANN) on Electro...
BACKGROUND AND AIMS: It is still controversial whether deep learning (DL) systems add accuracy to thyroid nodule imaging classification based on the recent available evidence. We conducted this study to analyze the current evidence of DL in thyroid n...
PURPOSE: To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.
RATIONALE AND OBJECTIVES: Recurrence of hepatocellular carcinoma (HCC) is a major concern in its management. Accurately predicting the risk of recurrence is crucial for determining appropriate treatment strategies and improving patient outcomes. A ce...
PURPOSE: This study aims to review deep learning applications for detecting head and neck cancer (HNC) using magnetic resonance imaging (MRI) and radiographic data.
OBJECTIVES: As an increasing number of studies apply artificial intelligence (AI) algorithms in osteoarthritis (OA) detection, we performed a systematic review and meta-analysis to pool the data on diagnostic performance metrics of AI, and to compare...
Oral surgery, oral medicine, oral pathology and oral radiology
Oct 16, 2023
OBJECTIVE: The study aim was to develop and assess the performance of a deep learning (DL) algorithm in the detection of radiolucent intraosseous jaw lesions in cone beam computed tomography (CBCT) volumes.
OBJECTIVES: To design a deep learning-based framework for automatic segmentation and detection of intracranial aneurysms (IAs) on magnetic resonance T1 images and test the robustness and performance of framework.
Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitoring of treatment response. Identification of acid-fast bacilli by fluorescence microscopy of sputum smears is a common tool for both tasks. Microscopy-b...
OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.
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