Oct 17,2019

Onco.com gets recognition from American Society of Clinical Oncology for online cancer guidance technology

Onco.com was felicitated for enhancement of cancer care at the American Society of Clinical Oncology (ASCO) conference, held at Bangkok, Thailand between October 11 and October 13, 2019. Onco.com is an Online Cancer Patient Assistance Pathway (OCPAP) built to help cancer patients get personalised treatment guidance as per international standardised protocols. The conference theme was “Breakthrough: A Global Summit for Oncology Innovators”.

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Oct 01,2019

Flatiron Health Announces Clinical Decision Support Application Through Epic’s App Orchard

Flatiron Health, a healthcare technology company focused on accelerating cancer research and improving patient care, announces the availability of its clinical decision support and pathways application, Flatiron Assist™, in the App Orchard. Available now in the App Orchard, Flatiron Assist™ is a SMART® on FHIR® application that will launch from the patient’s chart in Epic, eliminating the need for duplicate data entry outside the electronic medical record.

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Oct 31,2019

OncoHost: Nature Reviews Cancer Article Outlines Host Response Analysis as New Tool for Precision Medicine in Oncology

OncoHost, global leader in host response profiling for improved personalized cancer therapy, announced today that a review titled, The Pro-Tumorigenic Host Response To Cancer Therapies now appears in Nature Reviews Cancer.

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Nov 06,2019

Healius Limited goes live with DermEngine across Skin2 Clinics

Healius Limited has gone live with MetaOptima Technology’s DermEngine software across its Skin2 doctor-led service dedicated to the diagnosis and treatment of skin cancer. DermEngine’s cloud-based solution will provide the doctors who practice in Healius’clinics with an intelligent dermatology ecosystem for the imaging, documentation and diagnosis of skin conditions including skin cancer. Powered by artificial intelligence, this smart dermatology platform helps medical professionals manage busy workflows with secure cross-platform access for a targeted focus on enhanced patient outcomes.

COLLABORATION PARTNERSHIP

#institution

#ai/software

#platform

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Nov 20,2019

Belong.Life Broadens Global Impact With New Partners

Belong.Life has partnered with The Breast Health Foundation (BHF) and The Pink Parasol Project to provide support to breast cancer patients living in South Africa. Together, the organizations will work towards improving the quality of life for breast cancer patients by increasing access to authentic and trusted medical information, connecting individuals to medical and patient support communities and providing personalized tools to assist throughout the cancer journey.

COLLABORATION PARTNERSHIP

#institution

#mobile app

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Nov 11,2019

Hitachi and Centre Leon Berard Cancer Center in Lyon to Launch a Research Collaboration in the Fight Against Cancer with AI

Hitachi, Ltd. (TSE:6501) and Centre Leon Berard (CLB), a leading French Comprehensive Cancer Center in Lyon-France, announced that they have entered into an agreement to jointly promote research and development aimed at improving the efficiency of diagnosis and treatment of cancer and established a new research laboratory called Hitachi Lyon Lab on the CLB site, starting November 5th. In this collaboration, Hitachi and CLB will conduct research and development of novel technologies to detect and diagnose cancers exploiting medical images such as CT/MRI using artificial intelligence (AI) and to predict response to radiation therapy using tumor genomic and transcriptomic data.

COLLABORATION PARTNERSHIP

#r&d

#ai/software

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Nov 28,2019

Using Artificial Intelligence to Predict Risk of Thyroid Cancer on Ultrasound

Thyroid nodules are small lumps that form within the thyroid gland and are quite common in the general population, with a prevalence as high as 67%. The great majority of thyroid nodules are not cancerous and cause no symptoms. However, there are currently limited guidelines on what to do with a nodule when the risk of cancer is uncertain. A new study from The Sidney Kimmel Cancer Center - Jefferson Health investigates whether a non-invasive method of ultrasound imaging, combined with a Google-platform machine-learning algorithm, could be used as a rapid and inexpensive first screen for thyroid cancer.

CLINICAL STUDY

#ai/software

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Nov 27,2019

GE Healthcare Expands Intelligent Health Ecosystem with Launch of Edison Developer Program to Ease AI Adoption for Providers

Partners HealthCare and GE Healthcare are working together to improve the patient journey through co-development and integration of deep learning technology across the entire continuum of care under the Massachusetts General Hospital and Brigham and Women’s Hospital Center for Clinical Data Science. The collaboration currently includes 15 active projects underway within areas such as Women's Health, Cardiology, Oncology, Hospital Operations and Emergency Medicine, and relevant imaging modalities such as Computed Tomography (CT), Magnetic Resonance (MR) and Ultrasound (US).

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Dec 12,2019

Research shows that machine learning can be used to predict the onset and continuity of symptoms on patients receiving immune checkpoint inhibitor therapies

Kaiku Health and Oulu University Hospital have jointly published a research investigating the feasibility of machine learning in predicting symptoms of patients undergoing Immune Checkpoint Inhibitor (ICI) treatments. The study is the first of its kind and the results were published at the ESMO Immuno-Oncology Congress 2019 in Geneva on December 12. The results indicate that machine learning-based modeling of patient-reported symptom data on ICI treated cancer patients can predict the onset and continuity of symptoms related to ICI toxicities. The best performance considering all metrics was found for shortness of breath, joint pain, cough and fatigue. Importantly, all 14 symptom prediction models performed at a good level.

CLINICAL STUDY

#rwd

#ml

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Dec 05,2019

Kaiku Health presents research on machine learning-based prediction of symptoms at ESMO Immuno-Oncology Congress 2019

The abstract to be presented at the congress is based on research conducted in collaboration between Oulu University Hospital and Kaiku Health. The research investigates a method of utilizing advanced analytics and machine learning in order to predict the onset and continuity of symptoms in patients receiving immune checkpoint inhibitor treatments. The prediction model was developed by utilizing anonymized aggregated real-world patient-reported datasets collected with Kaiku Health.

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