AIMC Topic: Diagnosis, Differential
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The performance of deep learning on thyroid nodule imaging predicts thyroid cancer: A systematic review and meta-analysis of epidemiological studies with independent external test sets.
Diabetes & metabolic syndrome
Oct 25, 2023
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...
Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.
European radiology
Oct 11, 2023
OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.
An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis.
Scientific reports
Oct 3, 2023
Raman spectroscopy shows great potential as a diagnostic tool for thyroid cancer due to its ability to detect biochemical changes during cancer development. This technique is particularly valuable because it is non-invasive and label/dye-free. Compar...
Evaluating the Diagnostic Accuracy and Management Recommendations of ChatGPT in Uveitis.
Ocular immunology and inflammation
Sep 18, 2023
INTRODUCTION: Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice...
Does GPT-4 have neurophobia? Localization and diagnostic accuracy of an artificial intelligence-powered chatbot in clinical vignettes.
Journal of the neurological sciences
Sep 15, 2023
BACKGROUND AND OBJECTIVES: This is an observational study of the performance of an artificial intelligence-powered chatbot tasked with solving unknown neurologic case vignettes. The primary objective of the study is to assess the current capabilities...
ChatGPT and Generating a Differential Diagnosis Early in an Emergency Department Presentation.
Annals of emergency medicine
Sep 9, 2023
Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.
Journal of cancer research and clinical oncology
Sep 6, 2023
PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagnosed as renal cell carcinoma. We aimed to develop and evaluate a multichannel deep learning model for differentiating fat-poor angiomyolipoma (fp-AML)...
Data-driven decision-making for precision diagnosis of digestive diseases.
Biomedical engineering online
Sep 1, 2023
Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To ...
Deep Learning Radiomics Nomogram Based on Magnetic Resonance Imaging for Differentiating Type I/II Epithelial Ovarian Cancer.
Academic radiology
Aug 27, 2023
RATIONALE AND OBJECTIVES: To develop and validate a T2-weighted magnetic resonance imaging (MRI)-based deep learning radiomics nomogram (DLRN) to differentiate between type I and type II epithelial ovarian cancer (EOC).
Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.
Journal of biophotonics
Aug 23, 2023
The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep l...
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