AIMC Topic: Cancer Survivors
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Predictive Model to Identify the Long Time Survivor in Patients with Glioblastoma: A Cohort Study Integrating Machine Learning Algorithms.
Journal of molecular neuroscience : MN
Apr 25, 2024
We aimed to develop and validate a predictive model for identifying long-term survivors (LTS) among glioblastoma (GB) patients, defined as those with an overall survival (OS) of more than 3 years. A total of 293 GB patients from CGGA and 169 from TCG...
Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis.
Journal of cancer survivorship : research and practice
Dec 7, 2023
PURPOSE: To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim ...
Cancer survivorship care and general practice: A qualitative study of roles of general practice team members in Australia.
Health & social care in the community
Aug 22, 2021
Primary care providers, including general practice teams (GPTs), are well positioned within the community to integrate cancer survivorship care into ongoing health management. However, roles of GPT members in delivery of cancer survivorship care have...
Long-term cancer survival prediction using multimodal deep learning.
Scientific reports
Jun 29, 2021
The age of precision medicine demands powerful computational techniques to handle high-dimensional patient data. We present MultiSurv, a multimodal deep learning method for long-term pan-cancer survival prediction. MultiSurv uses dedicated submodels ...
Predicting anxiety in cancer survivors presenting to primary care - A machine learning approach accounting for physical comorbidity.
Cancer medicine
Jun 2, 2021
BACKGROUND: The purpose of this study was to explore predictors for anxiety as the most common form of psychological distress in cancer survivors while accounting for physical comorbidity.
Humans
Female
Aged
Comorbidity
Stress, Psychological
Primary Health Care
Regression Analysis
Breast Neoplasms
Male
Middle Aged
Anxiety
Muscle Weakness
Predictive Value of Tests
Sleep Initiation and Maintenance Disorders
Prostatic Neoplasms
Fatigue
Colonic Neoplasms
Cancer Pain
Supervised Machine Learning
Cancer Survivors
A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter.
BMC medical informatics and decision making
Dec 14, 2020
BACKGROUND: Emotions after surviving cancer can be complicated. The survivors may have gained new strength to continue life, but some of them may begin to deal with complicated feelings and emotional stress due to trauma and fear of cancer recurrence...
The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning.
Scientific reports
Jul 1, 2020
The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compar...
Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.
PloS one
Feb 27, 2020
The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two w...
Machine-learned identification of psychological subgroups with relation to pain interference in patients after breast cancer treatments.
Breast (Edinburgh, Scotland)
Feb 7, 2020
BACKGROUND: Persistent pain in breast cancer survivors is common. Psychological and sleep-related factors modulate perception, interpretation and coping with pain and may contribute to the clinical phenotype. The present analysis pursued the hypothes...
Predicting chemo-brain in breast cancer survivors using multiple MRI features and machine-learning.
Magnetic resonance in medicine
Nov 12, 2018
PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherapy drugs may result in brain damage during treatment. When a patient's brain is changed in response t...
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