AIMC Topic: Survival Analysis

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Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

International journal of cancer
Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRLM) to surgery or conservative therapy. However, there is no well-recognized method for predicting pa...

A meta-learning approach for genomic survival analysis.

Nature communications
RNA sequencing has emerged as a promising approach in cancer prognosis as sequencing data becomes more easily and affordably accessible. However, it remains challenging to build good predictive models especially when the sample size is limited and th...

A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction.

Scientific reports
Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent need ...

HIV-positive patients with oral Kaposi's sarcoma: An overall survival analysis of 31 patients.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: The aim of this study was to evaluate the influence of viral load and lymphocyte count on survival of patients who presented with human immunodeficiency virus (HIV)-associated oral Kaposi's sarcoma.

An Easy-to-Use Machine Learning Model to Predict the Prognosis of Patients With COVID-19: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Prioritizing patients in need of intensive care is necessary to reduce the mortality rate during the COVID-19 pandemic. Although several scoring methods have been introduced, many require laboratory or radiographic findings that are not a...

Deep Neural Networks for Survival Analysis Using Pseudo Values.

IEEE journal of biomedical and health informatics
There has been increasing interest in modelling survival data using deep learning methods in medical research. Current approaches have focused on designing special cost functions to handle censored survival data. We propose a very different method wi...

Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival.

Clinical physiology and functional imaging
INTRODUCTION: Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods ca...

A machine learning analysis of a "normal-like" IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets.

BMC medicine
BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis...