AIMC Topic: Cancer Survivors

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Applications of machine learning and natural language processing to neurocognitive outcomes in posttreatment cancer survivors: a scoping review.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This scoping review explores how machine learning (ML) and natural language processing (NLP) are used to detect, characterize, and predict neurocognitive symptoms in cancer survivors across age groups. The review had two goals: (1) to compar...

Cardiovascular Care in Pediatric Cancer Survivors: Updates on Risk, Prevention, and Therapies.

Current treatment options in oncology
Improved survival in pediatric oncology has highlighted the growing burden of cancer treatment-related cardiotoxicity among survivors of childhood cancers. While the cardiotoxicity of anthracyclines and chest radiation are well documented as major co...

Evaluation of Cancer Survivors' Experience of Using AI-Based Conversational Tools: Qualitative Study.

JMIR cancer
BACKGROUND: Cancer survivorship is a complicated, chronic, and long-lasting experience, causing uncertainty and a wide range of physical and emotional health concerns. Due to the complexity of cancer, patients often seek out multiple sources of healt...

Harnessing artificial intelligence for cancer rehabilitation: A call to action.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Recent evidence from the CHALLENGE trial confirms that structured exercise can significantly improve survival outcomes in colon cancer survivors, reinforcing the principle that exercise is medicine. However, implementing personalized and scalable reh...

Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, and Validation Study.

JMIR cancer
BACKGROUND: Complementary therapies are being increasingly used by cancer survivors. As a channel for customers to share their feelings, outcomes, and perceived knowledge about the products purchased from e-commerce platforms, Amazon consumer reviews...

INDIGO randomised controlled digital clinical trial: INvestigating DIgital outcomes and quality of life in cancer survivors - a study protocol.

BMJ open
INTRODUCTION: There are estimated to be 3.4 million patients in the UK living after a diagnosis of cancer. We know very little about their quality of life or healthcare usage. Patient-reported outcome measures (PROMs) are tools which help to translat...

The critical effects of self-management strategies on predicting cancer survivors' future quality of life and health status using machine learning techniques.

PloS one
Despite the significance of enhancing the quality of life (QoL) and overall health status (including physical, mental, social, and spiritual well-being) among individuals who have survived cancer, the existing prediction model for QoL and health stat...

Cancer care coordination determinants of depression in head and neck cancer survivors.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aims to explore the role of patient-reported cancer care coordination in explaining depression among head and neck (HNC) cancer survivors.

A machine learning approach to predict self-efficacy in breast cancer survivors.

BMC medical informatics and decision making
PURPOSE: To determine predictors of self-efficacy in breast cancer survivors and identify vulnerable groups.

Development and Validation of a Novel Prediction Model for Hearing Loss From Cisplatin Chemotherapy.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Cisplatin treats many common tumors but causes permanent and debilitating hearing loss (HL). The objective of this study was to develop and externally validate a predictive model of HL in cisplatin-treated children and adolescent cancer surv...