May 20,2021

2021 ASCO Annual Meeting Publishes Two Abstracts Based on Real-World Patient Data Generated from Belong.Life's Connected Health Platform

Belong.Life, developer of social and professional networks for managing and navigating diseases, and the creator of the world's largest social network for cancer patients, today announced that the American Society of Clinical Oncology (ASCO) has published two abstracts in its 2021 Annual Meeting Abstract Book based on data aggregated from the Belong Beating Cancer Together app. The abstracts provide key insights into significant challenges for oncology patients, including sexuality and clinical trial participation.

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May 24,2021

Grand Challenge Research Harnesses AI to Fight Breast Cancer

Breast cancer has recently overtaken lung cancer to become the most common cancer globally, according to the World Health Organization. Advancing the fight against breast cancer, the BreastPathQ Challenge was launched at SPIE Medical Imaging 2019 to support the development of computer-aided diagnosis for assessing breast cancer pathology.

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#ai/software

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May 08,2021

Impact of assessment frequency of patient-reported outcomes: an observational study using an eHealth platform in cancer patients

The evaluation of patient-reported outcomes (PRO) in cancer has proven relevant positive clinical impact on patients’ communication with healthcare professionals, decision-making for management, well-being, and overall survival. However, the optimal frequency of PRO assessment has yet to be defined. Based on the assumption that more frequent sampling would enhance accuracy, the study aimed at identifying the optimal sampling frequency that does not miss clinically relevant insight.

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#platform

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May 28,2021

Increasing physical activity in Cancer Survivors through a Text-messaging Exercise motivation Program (ICanSTEP)

Cancer survivors are often sedentary. Self-monitoring may promote physical activity through self-activation. The researchers conducted a pilot trial to evaluate whether wearable activity tracker with personalized text message feedback would increase physical activity. Each participant received an activity tracker and daily text messages personalized to their activity level. The results showed that the intervention was well-accepted with a high completion rate at 3 months and continued self-use at 6 months.

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Jun 07,2021

Perceptions and acceptance of telemedicine among medical oncologists before and during the COVID-19 pandemic in Turkey

As a result of technological developments in healthcare services, telemedicine is becoming widespread. The study aimed to determine the effect of COVID-19 on Turkish medical oncologists’ opinions of telemedicine through a survey.

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#telehealth

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Jun 10,2021

Lessons learned about virtual cancer care and distress screening in the time of COVID-19

Cancer-related biopsychosocial distress is highly prevalent across the cancer care continuum. The implementation of screening patients for biopsychosocial distress has become a standard of practice in cancer care. With the presence of COVID-19, clinical care has shifted from in-person care to virtual care in many instances. One of the realities of COVID-19 is the significant decrease in screening patients for biopsychosocial symptom burden. Given the presence of COVID-19, much of cancer care has shifted to being delivered virtually (through mediums such as Zoom). This paper presents pre- and post-COVID data on the frequency of distress screening and its impact on patient care.

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Jul 08,2021

Disparities in access to mobile devices and e-health literacy among breast cancer survivors

The number of e-health interventions developed for breast cancer survivors continues to increase. However, issues with engagement and retention are common. This study aimed to explore e-health literacy rates and access to smartphones and tablets in a large sample of breast cancer survivors.

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#mobile app

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Jul 22,2021

Artificial Intelligence Models to Analyze Cancer Images Take Shortcuts that Introduce Bias

Artificial intelligence tools and deep learning models are a powerful tool in cancer treatment. They can be used to analyze digital images of tumor biopsy samples, helping physicians quickly classify the type of cancer, predict prognosis and guide a course of treatment for the patient. However, unless these algorithms are properly calibrated, they can sometimes make inaccurate or biased predictions. A new study led by researchers from the University of Chicago shows that deep learning models trained on large sets of cancer genetic and tissue histology data can easily identify the institution that submitted the images.

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#ai/software

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Jul 05,2021

The role of teledentistry in oral cancer patients during the COVID-19 pandemic: an integrative literature review

This integrative review aimed to assess the benefits of the use of teledentistry for patients undergoing treatment of oral and head and neck cancer during the COVID-19 pandemic.

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#telehealth

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Jul 13,2021

A hybrid method of healthcare delivery research and human-centered design to develop technology-enabled support for caregivers of hematopoietic stem cell transplant recipients

Health information technology (HIT) is a widely recognized strategy to encourage cancer patients and caregivers to participate in healthcare delivery in a sustainable and cost-effective way. In the context of autologous hematopoietic cell transplant (HSCT), HIT-enabled tools have the potential to effectively engage, educate, support, and optimize outcomes of patients and caregivers in the outpatient setting. This study sought to leverage human-centered design to develop a high-fidelity prototype of a HIT-enabled psychoeducational tool for HSCT caregivers.

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