AIMC Topic: Retrospective Studies

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Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.

Applied clinical informatics
BACKGROUND: Thirty-day hospital readmissions are a quality metric for health care systems. Predictive models aim to identify patients likely to readmit to more effectively target preventive strategies. Many risk of readmission models have been develo...

Comparison of robot-assisted modified radical neck dissection using a bilateral axillary breast approach with a conventional open procedure after propensity score matching.

Surgical endoscopy
BACKGROUND: There is ongoing debate about whether or not robot-assisted thyroidectomy is appropriate for modified radical neck dissection (MRND). The purpose of this study was to compare the surgical outcomes of robot-assisted MRND with those of a co...

A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction.

Radiology
Background Mammographic density improves the accuracy of breast cancer risk models. However, the use of breast density is limited by subjective assessment, variation across radiologists, and restricted data. A mammography-based deep learning (DL) mod...

Declining use of radical prostatectomy and pelvic lymphadenectomy despite more robotics: National population data over 15 years.

Asia-Pacific journal of clinical oncology
AIM: To describe national surgical patterns of prostate cancer (PCa) care considering radical prostatectomy with or without pelvic lymphadenectomy and consideration of robotic-assisted techniques.

Deep learning-based survival prediction of oral cancer patients.

Scientific reports
The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covaria...

Dynamic contrast-enhanced computed tomography diagnosis of primary liver cancers using transfer learning of pretrained convolutional neural networks: Is registration of multiphasic images necessary?

International journal of computer assisted radiology and surgery
PURPOSE: To evaluate the effect of image registration on the diagnostic performance of transfer learning (TL) using pretrained convolutional neural networks (CNNs) and three-phasic dynamic contrast-enhanced computed tomography (DCE-CT) for primary li...

Performance of a Deep Learning Model vs Human Reviewers in Grading Endoscopic Disease Severity of Patients With Ulcerative Colitis.

JAMA network open
IMPORTANCE: Assessing endoscopic disease severity in ulcerative colitis (UC) is a key element in determining therapeutic response, but its use in clinical practice is limited by the requirement for experienced human reviewers.

Diagnostic ability of artificial intelligence using deep learning analysis of cyst fluid in differentiating malignant from benign pancreatic cystic lesions.

Scientific reports
The diagnosis of pancreatic cystic lesions remains challenging. This study aimed to investigate the diagnostic ability of carcinoembryonic antigen (CEA), cytology, and artificial intelligence (AI) by deep learning using cyst fluid in differentiating ...

Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine.

EBioMedicine
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating disease with high mortality rate. This study aimed to predict hematoma expansion in spontaneous ICH from routinely available variables by using support vector machine (SVM) metho...