AI Medical Compendium Topic:
Follow-Up Studies

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Predicting Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Standardized and robust risk-stratification systems for patients with hepatocellular carcinoma (HCC) are required to improve therapeutic strategies and investigate the benefits of adjuvant systemic therapies after curative resect...

Robot-assisted minimally invasive thoracolaparoscopic esophagectomy versus open esophagectomy: long-term follow-up of a randomized clinical trial.

Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus
Initial results of the ROBOT, which randomized between robot-assisted minimally invasive esophagectomy (RAMIE) and open transthoracic esophagectomy (OTE), showed significantly better short-term postoperative outcomes in favor of RAMIE. However, it is...

Machine learning-based prediction of outcomes of the endoscopic endonasal approach in Cushing disease: is the future coming?

Neurosurgical focus
OBJECTIVE: Machine learning (ML) is an innovative method to analyze large and complex data sets. The aim of this study was to evaluate the use of ML to identify predictors of early postsurgical and long-term outcomes in patients treated for Cushing d...

Developments in the follow-up of nonmuscle invasive bladder cancer: what did we learn in the last 24 months: a critical review.

Current opinion in urology
PURPOSE OF REVIEW: Patients with nonmuscle invasive bladder cancer (NMIBC) have a high risk of recurrent tumors, even in spite of contemporary guideline recommended therapy. Follow-up recommendations are also clear (cystoscopy with cytology and upper...

Automated Detection of Radiology Reports that Require Follow-up Imaging Using Natural Language Processing Feature Engineering and Machine Learning Classification.

Journal of digital imaging
While radiologists regularly issue follow-up recommendations, our preliminary research has shown that anywhere from 35 to 50% of patients who receive follow-up recommendations for findings of possible cancer on abdominopelvic imaging do not return fo...