Aug 28,2020

A COVID-19 screening tool for oncology telephone triage

Symptoms associated with COVID-19 infection have made the assessment and triage of cancer patients extremely complicated. The purpose of this paper is to describe the development and implementation of a COVID-19 screening tool for oncology telephone triage.

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Sep 25,2020

An App Monitors Cancer Patients' Health Status and Rewards Participation

Close2U, an electronic device application, has been developed by researchers at the Complutense University (UCM) and the University of Zaragoza (UZA) to monitor cancer patients' physical and mental health using gamification. Users answer a series of daily questions about their mood and where they are experiencing pain. In return, the app rewards them in the form of advice or songs, resources intended to increase their motivation.

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#mobile app

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Sep 12,2020

Cancer patient perspectives on survivorship goals from the Smart Patients online community

Cancer impacts individuals’ life goals. Recent cancer care guidelines recommend discussing life goals as part of patient-provider communication. The goal of this study was to understand patients’ attitudes toward goal sharing with their cancer care providers.

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#telehealth

#coaching

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Sep 23,2020

Development and evaluation of a sustainable video health education program for newly diagnosed breast cancer patients in Malaysia

Wider breast cancer (BC) treatment options, short consultation time with physicians, lack of knowledge, and poor coping skills at the time of diagnosis may affect patients’ decisions causing treatment delays and non-adherence. To address this gap, a breast care nurse video orientation program was started. The aim was to evaluate the video on patients’ knowledge, satisfaction, and treatment adherence.

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#telehealth

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Nov 24,2020

Smartphone measurements of physical activity and fitness are associated with early trial discontinuation of patients in (hemato)oncology phase I/II clinical trials

Patients, who discontinue early, do not benefit from phase I/II clinical trials (early-phase clinical trials (EPCT)). In this study, associations between objective smartphone measurements of physical activity and fitness and early trial discontinuation in patients with cancer participating in EPCT were investigated.

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#mobile app

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Nov 04,2020

Oncohost platform improves immunotherapy response predictions

By analyzing patients’ reactions to treatment, Oncohost Ltd.’s proteomics-based platform enables earlier prediction of paradoxical responses to immunotherapy that promote tumor growth in certain cancers. The artificial intelligence-powered host response profiling platform, called Prophet, could help identify the best combination of therapies and minimize adverse effects from treatments that are unlikely to be beneficial.

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#ai/software

#platform

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Dec 17,2020

Kaiku Health has taken its first steps to predict treatment response of cancer patients for immune checkpoint inhibitor therapies with machine learning

Kaiku Health has taken its first steps to tackle the big issue related to the challenge of identifying which patients are likely to benefit from immune checkpoint inhibitor (ICI) therapies. In collaboration with Oulu University Hospital (OYS), Kaiku Health conducted a study which investigated whether machine learning (ML) could be used to predict the treatment response, or more specifically objective response rate (ORR) of ICI treated patients, based on clinical and patient-reported data. ORR was defined as the proportion of patients in whom partial (PR) or complete (CR) responses were seen as the best overall response. The results of this study were presented at the ESMO IO 2020 Virtual Congress last week and received remarkable attention from the European Society for Medical Oncology.

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#ml

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Dec 07,2020

Predicting patient-reported symptoms for cancer patients undergoing immune checkpoint inhibitor (ICI) therapies using different measurement system than in prediction model training

Kaiku has continued its work among building machine learning (ML) based prediction models for immunotherapy-related symptom development. A year ago results from the first study were presented in the ESMO IO congress 2019 where it was showcased that ML based modeling of ePRO data on ICI treated cancer patients is feasible in predicting the onset and continuation of symptoms related to ICI toxicities. Now, in a study conducted together with Dr.med Razvan Popescu & Tumor Zentrum Aarau from Switzerland it was proven that the previously built models generalize well to data collected using different symptom measurement system (PRO-CTCAE) in a different geographical area. The results are promising and Kaiku and Tumor Zentrum Aarau plan to continue the joint research.

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#ml

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Jan 24,2019

Real-World Data based on Kaiku Health Immune Checkpoint Inhibitor Module published in Journal of Cancer Research and Clinical Oncology

Kaiku Health, Oulu University Hospital and Docrates Cancer Center have published first data on the symptoms reported by cancer patients receiving immune checkpoint inhibitor (ICI) therapies in a real-world setting. This study shows that utilizing digital symptom tracking is feasible in better engaging patients in symptom self-reporting during ICI treatments. This helps in gaining a more comprehensive understanding on the onset and presence of immune-related adverse events.

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#ml

#rwd

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Jan 11,2019

AI Approach Outperformed Human Experts in Identifying Cervical Precancer

A research team led by investigators from the National Institutes of Health and Global Good has developed a computer algorithm that can analyze digital images of a woman's cervix and accurately identify precancerous changes that require medical attention. This artificial intelligence (AI) approach, called automated visual evaluation, has the potential to revolutionize cervical cancer screening, particularly in low-resource settings.

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#ai/software

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