AIMC Topic: Prognosis

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Impact of Tumor Location on Predicting Early-Stage Breast Cancer Patient Survivability Using Explainable Machine Learning Models.

JCO clinical cancer informatics
PURPOSE: This study aims to investigate the impact of tumor quadrant location on the 5-year early-stage breast cancer survivability prediction using explainable machine learning (ML) models. By integrating these predictive models with Shapley Additiv...

Multiomics evaluation and machine learning optimize molecular classification, prediction of prognosis and immunotherapy response for ovarian cancer.

Pathology, research and practice
BACKGROUND: Ovarian cancer (OC), owing to its substantial heterogeneity and high invasiveness, has historically been devoid of precise, individualized treatment options. This study aimed to establish integrated consensus subtypes of OC using differen...

Prognostic value of SAPS II score for 28-day mortality in ICU patients with acute pulmonary embolism.

International journal of cardiology
BACKGROUND: Acute pulmonary embolism (APE) is a common and life-threatening emergency in intensive care units (ICUs). Effective risk assessment tools are essential to improve patient outcomes. This study aims to evaluate the association between Simpl...

Artificial intelligence-based multimodal prediction for nuclear grading status and prognosis of clear cell renal cell carcinoma: a multicenter cohort study.

International journal of surgery (London, England)
BACKGROUND: The assessment of the International Society of Urological Pathology (ISUP) nuclear grade is crucial for the management and treatment of clear cell renal cell carcinoma (ccRCC). This study aimed to explore the value of using integrated mul...

Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries.

Scientific reports
The most prevalent malignancy among women is breast cancer; hence, treatment approaches are needed in consideration of tumor characteristics and disease stage but also patient preference. Two surgical options, Mastectomy and Breast Conserving Surgery...

Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.

Scientific reports
This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney injury (AKI) in diabetic patients with heart failure (HF) during hospitalization. Using data from 1,457 patients in the MIMIC-IV database, the study ide...

Machine learning based intratumor heterogeneity related signature for prognosis and drug sensitivity in breast cancer.

Scientific reports
Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity shows discrepancy in different breast cancer (BRCA) patients due to ITH. The genes mediating ITH in BRCA and their role in predicting prognosis and dr...

Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach.

JMIR medical informatics
BACKGROUND: Chronic pain is a complex condition that affects more than a quarter of people worldwide. The development and progression of chronic pain are unique to each individual due to the contribution of interacting biological, psychological, and ...

A prediction model based on machine learning: prognosis of HBV-induced HCC male patients with smoking and drinking habits after local ablation treatment.

Frontiers in immunology
BACKGROUND: Liver cancer, particularly hepatocellular carcinoma (HCC), is a major health concern globally and in China, possibly shows recurrence after ablation treatment in high-risk patients. This study investigates the prognosis of early-stage mal...