AIMC Topic: Diagnosis, Differential
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Effect of artificial intelligence-aided differentiation of adenomatous and non-adenomatous colorectal polyps at CT colonography on radiologists' therapy management.
European radiology
Jan 25, 2025
OBJECTIVES: Adenomatous colorectal polyps require endoscopic resection, as opposed to non-adenomatous hyperplastic colorectal polyps. This study aims to evaluate the effect of artificial intelligence (AI)-assisted differentiation of adenomatous and n...
Aged
Aged, 80 and over
Adult
Sensitivity and Specificity
Humans
Artificial Intelligence
Retrospective Studies
Female
Radiologists
Radiographic Image Interpretation, Computer-Assisted
Colonic Polyps
Adenomatous Polyps
Colonography, Computed Tomographic
Colorectal Neoplasms
Male
Middle Aged
Diagnosis, Differential
Machine learning demonstrates clinical utility in distinguishing retinoblastoma from pseudo retinoblastoma with RetCam images.
Ophthalmic genetics
Jan 20, 2025
BACKGROUND: Retinoblastoma is diagnosed and treated without biopsy based solely on appearance (with the indirect ophthalmoscope and imaging). More than 20 benign ophthalmic disorders resemble retinoblastoma and errors in diagnosis continue to be made...
Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.
La Radiologia medica
Jan 20, 2025
BACKGROUND: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography (CT) images t...
Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.
Neuroradiology
Jan 18, 2025
INTRODUCTION: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI a...
Development of a clinical prediction model for benign and malignant pulmonary nodules with a CTR ≥ 50% utilizing artificial intelligence-driven radiomics analysis.
BMC medical imaging
Jan 17, 2025
OBJECTIVE: In clinical practice, diagnosing the benignity and malignancy of solid-component-predominant pulmonary nodules is challenging, especially when 3D consolidation-to-tumor ratio (CTR) ≥ 50%, as malignant ones are more invasive. This study aim...
Can ChatGPT 4.0 Diagnose Acute Aortic Dissection? Integrating Artificial Intelligence into Medical Diagnostics.
The American journal of cardiology
Jan 16, 2025
Acute aortic dissection (AD) is a critical condition characterized by high mortality and frequent misdiagnoses, primarily due to symptom overlap with other medical pathologies. This study explores the diagnostic utility of ChatGPT 4.0, an artificial ...
Automated analysis of spoken language differentiates multiple system atrophy from Parkinson's disease.
Journal of neurology
Jan 15, 2025
BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis o...
Deep Learning Radiomics Nomogram Based on MRI for Differentiating between Borderline Ovarian Tumors and Stage I Ovarian Cancer: A Multicenter Study.
Academic radiology
Jan 14, 2025
RATIONALE AND OBJECTIVES: To develop and validate a deep learning radiomics nomogram (DLRN) based on T2-weighted MRI to distinguish between borderline ovarian tumors (BOTs) and stage I epithelial ovarian cancer (EOC) preoperatively.
Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis.
Scientific reports
Jan 14, 2025
The conventional statistical approach for analyzing resting state functional MRI (rs-fMRI) data struggles to accurately distinguish between patients with multiple sclerosis (MS) and those with neuromyelitis optic spectrum disorders (NMOSD), highlight...
The use of a ChatGPT-4-based chatbot in teledermatology: A retrospective exploratory study.
Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG
Jan 12, 2025
BACKGROUND AND OBJECTIVES: Integration of artificial intelligence in healthcare, particularly ChatGPT, is transforming medical diagnostics and may benefit teledermatology. This exploratory study compared image description and differential diagnosis g...
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