AIMC Topic: Retrospective Studies

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Deep learning model for automatic differentiation of EMAP from AMD in macular atrophy.

Scientific reports
To create a deep learning (DL) classifier pre-trained on fundus autofluorescence (FAF) images that can assist the clinician in distinguishing age-related geographic atrophy from extensive macular atrophy and pseudodrusen-like appearance (EMAP). Patie...

Prediction of Parkinson's disease by transcranial sonography-based deep learning.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
OBJECTIVES: Transcranial sonography has been used as a valid neuroimaging tool to diagnose Parkinson's disease (PD). This study aimed to develop a modified transcranial sonography (TCS) technique based on a deep convolutional neural network (DCNN) mo...

Machine learning detects symptomatic patients with carotid plaques based on 6-type calcium configuration classification on CT angiography.

European radiology
OBJECTIVES: While the link between carotid plaque composition and cerebrovascular vascular (CVE) events is recognized, the role of calcium configuration remains unclear. This study aimed to develop and validate a CT angiography (CTA)-based machine le...

Large-scale pancreatic cancer detection via non-contrast CT and deep learning.

Nature medicine
Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental detection is associated with prolonged survival, but screening asymptomatic individuals for PDAC usi...

Oncologic outcomes of robot-assisted laparoscopy versus conventional laparoscopy for the treatment of apparent early-stage endometrioid adenocarcinoma of the uterus.

Gynecologic oncology
OBJECTIVE: To compare long-term oncologic outcomes in patients with clinically uterine-confined endometrioid endometrial cancer who underwent surgical staging with robot-assisted (RA) versus conventional laparoscopy.

PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.

Nature communications
Occult nodal metastasis (ONM) plays a significant role in comprehensive treatments of non-small cell lung cancer (NSCLC). This study aims to develop a deep learning signature based on positron emission tomography/computed tomography to predict ONM of...

Should All Pancreatic Cystic Lesions with Worrisome or High-Risk Features Be Resected? A Clinical and Radiological Machine Learning Model May Help to Answer.

Academic radiology
RATIONALE AND OBJECTIVES: According to current guidelines, pancreatic cystic lesions (PCLs) with worrisome or high-risk features may have overtreatment. The purpose of this study was to build a clinical and radiological based machine-learning (ML) mo...

Creation of a Novel, Race-Adjusted, and Risk-Adapted Scoring System to Predict Positive Surgical Margins and Prolonged Operative Time During Robotic Radical Prostatectomy.

Journal of endourology
To compare racial differences and pelvis dimensions between Caucasians and African Americans (AAs) and to develop a risk calculator and scoring system to predict the risk of prolonged operative time and presence of positive surgical margins (PSM) ba...