AIMC Topic: Prognosis

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Development of a predictive model for distant metastasis in HCC patients post-TACE using clinical data, radiomics, and deep learning.

Journal of cancer research and clinical oncology
PURPOSE: Hepatocellular carcinoma (HCC) is a perilous malignant tumor, and transcatheter arterial chemoembolization (TACE) is a widely adopted treatment technique for advanced HCC. Nevertheless, TACE may not effectively reduce the risk of distant met...

Development of a prostate cancer biochemical recurrence risk signature using machine learning and motor protein-related genes.

PloS one
BACKGROUND: Motor proteins play significant roles in cancer progression, but their involvement in biochemical recurrence (BCR) of prostate cancer remains unclear. The objective of the study is to develop a prognostic indicator for BCR using machine l...

Effect of immune-related intratumoral microbiota and host gene expression on cancer prognosis.

mSystems
UNLABELLED: The intratumoral microbiota has been identified as an indispensable part of the tumor microenvironment (TME). However, the relationship between the intratumoral microbiota and host gene expression, as well as its impact on prognosis and T...

Construction and multi-omics analysis of ccRCC mitochondrial related gene machine learning model and validate of key gene FKBP10.

International immunopharmacology
BACKGROUND: Clear cell renal cell carcinoma represents the most prevalent histological subtype of renal malignancy Emerging evidence underscores the critical involvement of mitochondrial dysfunction in oncogenesis and tumor progression. In this study...

Prognostic models for radiation-induced complications after radiotherapy in head and neck cancer patients.

The Cochrane database of systematic reviews
BACKGROUND: Radiotherapy is the mainstay of treatment for head and neck cancer (HNC) but may induce various side effects on surrounding normal tissues. To reach an optimal balance between tumour control and toxicity prevention, normal tissue complica...

Predicting In-Hospital Cardiac Arrest Using Machine Learning Models: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: In-hospital cardiac arrest (IHCA) remains a public health conundrum with high morbidity and mortality rates. While early identification of high-risk patients could enable preventive interventions and improve survival, evidence on the effe...

Predicting mortality dynamics in cancer patients: A machine learning approach to pre-death events.

PloS one
Capturing the dynamic changes in patients' internal states as they approach death due to fatal diseases remains a major challenge in understanding individual pathologies and improving end-of-life care. However, existing methods primarily focus on spe...

Machine learning-based prediction model for 28-day mortality in acute kidney injury patients with liver cirrhosis: A MIMIC-IV database analysis.

PloS one
BACKGROUND: Acute kidney injury (AKI) in patients with liver cirrhosis represents a significant clinical challenge with high mortality rates. This study aimed to develop and validate a machine learning-based prediction model for 28-day mortality in A...

VO Max in Clinical Cardiology: Clinical Applications, Evidence Gaps, and Future Directions.

Current cardiology reports
PURPOSE OF REVIEW: VO₂ max is a fundamental marker of cardiorespiratory fitness with substantial prognostic and diagnostic value within the field of cardiology. This review analyzes current and emerging evidence regarding its clinical uses, highlight...

Recognition of molecular clusters and a novel prognostic signature based on natural killer cell-related genes in skin cutaneous melanoma.

World journal of surgical oncology
BACKGROUND: Skin cutaneous melanoma (SKCM) is the third most common type of cutaneous malignant tumor with a poor prognosis. This research aimed to recognize molecular clusters and develop a novel prognostic signature based on natural killer (NK) cel...