AIMC Topic: Diagnosis, Differential

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Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Translational psychiatry
Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in misdiagnosis and suboptimal treatment outcomes. This study aimed to identify EEG-based biomarkers tha...

Deep Learning Approach Readily Differentiates Papilledema, Non-Arteritic Anterior Ischemic Optic Neuropathy, and Healthy Eyes.

American journal of ophthalmology
OBJECTIVE: Deep learning (DL) has been used in differentiating a range of ophthalmic conditions. We describe a model to distinguish among fundus photos of acquired optic disc swelling due to idiopathic intracranial hypertension (IIH), non-arteritic a...

Evaluating medical AI systems in dermatology under uncertain ground truth.

Medical image analysis
For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However, in medical applications, this ground truth is often curated in the f...

Towards accurate differential diagnosis with large language models.

Nature
A comprehensive differential diagnosis is a cornerstone of medical care that is often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures. Interactive interfaces p...

An artificial intelligence model utilizing endoscopic ultrasonography for differentiating small and micro gastric stromal tumors from gastric leiomyomas.

BMC gastroenterology
BACKGROUND: Gastric stromal tumors (GSTs) and gastric leiomyomas (GLs) represent the primary subtypes of gastric submucosal tumors (SMTs) characterized by distinct biological characteristics and treatment modalities. The accurate differentiation betw...

FreqYOLO: A uterine disease detection network based on local and global frequency feature learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Leiomyomas (LM) and adenomyosis (AM) are common gynecological diseases with high incidence rates and an increasing trend of affecting younger women. Accurate detection and differentiation of LM and AM in ultrasound images are crucial for selecting ap...

DeepSeek-R1 and GPT-4 are comparable in a complex diagnostic challenge: a historical control study.

International journal of surgery (London, England)
BACKGROUND: Large language models (LLMs) have demonstrated potential in medical diagnostics, but their accuracy in complex cases remains a subject of investigation. DeepSeek-R1, an open-source model with advanced reasoning capabilities, has gained gl...

Pancreatic Cancer Detection and Differentiation from Chronic Pancreatitis: Potential Biomarkers Identified through a High-Throughput Multiplex Proteomic Assay and Machine Learning-Based Analysis.

Annals of laboratory medicine
BACKGROUND: Pancreatic cancer (PC)-screening methods have limited accuracy despite their high clinical demand. Differential diagnosis of chronic pancreatitis (CP) poses another challenge for PC diagnosis. Therefore, we aimed to identify blood protein...

Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal of digestive diseases
OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.

Multiparametric MRI-based Interpretable Machine Learning Radiomics Model for Distinguishing Between Luminal and Non-luminal Tumors in Breast Cancer: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: To construct and validate an interpretable machine learning (ML) radiomics model derived from multiparametric magnetic resonance imaging (MRI) images to differentiate between luminal and non-luminal breast cancer (BC) subtyp...