AIMC Topic: Follow-Up Studies

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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...

Evaluation of Prognosis in Nasopharyngeal Cancer Using Machine Learning.

Technology in cancer research & treatment
BACKGROUND AND AIM: Although the prognosis of nasopharyngeal cancer largely depends on a classification based on the tumor-lymph node metastasis staging system, patients at the same stage may have different clinical outcomes. This study aimed to eval...

Development and Assessment of a Machine Learning Model to Help Predict Survival Among Patients With Oral Squamous Cell Carcinoma.

JAMA otolaryngology-- head & neck surgery
IMPORTANCE: Predicting survival of oral squamous cell carcinoma through the use of prediction modeling has been underused, and the development of prediction models would augment clinicians' ability to provide absolute risk estimates for individual pa...

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography.

European heart journal
BACKGROUND: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). Howeve...

Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand can...