AIMC Topic: Prognosis

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Automatic detection of circulating tumor cells and cancer associated fibroblasts using deep learning.

Scientific reports
Circulating tumor cells (CTCs) and cancer-associated fibroblasts (CAFs) from whole blood are emerging as important biomarkers that potentially aid in cancer diagnosis and prognosis. The microfilter technology provides an efficient capture platform fo...

Systematic review finds "spin" practices and poor reporting standards in studies on machine learning-based prediction models.

Journal of clinical epidemiology
OBJECTIVES: We evaluated the presence and frequency of spin practices and poor reporting standards in studies that developed and/or validated clinical prediction models using supervised machine learning techniques.

Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level.

Ultrasonics
Automated ultrasound imaging assessment of the effect of CoronaVirus disease 2019 (COVID-19) on lungs has been investigated in various studies using artificial intelligence-based (AI) methods. However, an extensive analysis of state-of-the-art Convol...

Imaging of Neck Nodes in Head and Neck Cancers - a Comprehensive Update.

Clinical oncology (Royal College of Radiologists (Great Britain))
Cervical lymph node metastases from head and neck squamous cell cancers significantly reduce disease-free survival and worsen overall prognosis and, hence, deserve more aggressive management and follow-up. As per the eighth edition of the American Jo...

Integrating single-cell analysis and machine learning to create glycosylation-based gene signature for prognostic prediction of uveal melanoma.

Frontiers in endocrinology
BACKGROUND: Increasing evidence suggests a correlation between glycosylation and the onset of cancer. However, the clinical relevance of glycosylation-related genes (GRGs) in uveal melanoma (UM) is yet to be fully understood. This study aimed to shed...

Preoperative endogenous total testosterone predicts prostate cancer progression: results in 580 consecutive patients treated with robot assisted radical prostatectomy for clinically localized disease.

International urology and nephrology
PURPOSE: To test the role of endogenous total testosterone (ETT) as a predictor of prostate cancer (PCa) progression in patients treated with robot assisted radical prostatectomy for clinically localized disease.

Predicting outcomes of continuous renal replacement therapy using body composition monitoring: a deep-learning approach.

Scientific reports
Fluid balance is a critical prognostic factor for patients with severe acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT). This study evaluated whether repeated fluid balance monitoring could improve prognosis in this cli...

Comparison of a machine and deep learning model for automated tumor annotation on digitized whole slide prostate cancer histology.

PloS one
One in eight men will be affected by prostate cancer (PCa) in their lives. While the current clinical standard prognostic marker for PCa is the Gleason score, it is subject to inter-reviewer variability. This study compares two machine learning metho...