AI Medical Compendium Topic

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Preoperative Period

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Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma.

BMC cancer
BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated wit...

Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images.

Breast cancer research : BCR
BACKGROUND: Nottingham histological grade (NHG) is a well established prognostic factor in breast cancer histopathology but has a high inter-assessor variability with many tumours being classified as intermediate grade, NHG2. Here, we evaluate if Dee...

Reliable prediction of implant size and axial alignment in AI-based 3D preoperative planning for total knee arthroplasty.

Scientific reports
The size and axial alignment of prostheses, when planned during total knee replacement (TKA) are critical for recovery of knee function and improvement of knee pain symptoms. This research aims to study the effect of artificial intelligence (AI)-base...

Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

Thoracic cancer
BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar resection for the surgical treatment of small lung cancers, preoperative identification of this subtype...

The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: a multicenter cohort study.

International journal of surgery (London, England)
BACKGROUND: The increasing use of kidneys from elderly donors raises concerns due to age-related nephron loss. Combined with nephrectomy, this loss of nephrons markedly increases the risk of developing chronic kidney disease (CKD). This study aimed t...

Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models.

Indian journal of ophthalmology
PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.

Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.

Journal of medical Internet research
BACKGROUND: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic morta...

Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies according to risk. However, no specific protocols exist for preoperative assessment of the malignant potential of gastric GISTs (gGISTs). This study ai...

Artificial Intelligence-Based Assessment of Preoperative Body Composition Is Associated With Early Complications After Radical Cystectomy.

The Journal of urology
PURPOSE: We aimed to use a validated artificial intelligence (AI) algorithm to extract muscle and adipose areas from CT images before radical cystectomy (RCx) and then correlate these measures with 90-day post-RCx complications.