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Radiomic Algorithm Predicts if Patient’s Cancer Can Return 10 Years After Treatment

 A new study by researchers at Penn Medicine (Philadelphia, PA, USA) has found that Magnetic Resonance Imaging (MRI) and an emerging field of medicine called radiomics — which uses algorithms to extract a large amount of features from medical images — could help to characterize the heterogeneity of cancer cells within a tumor and allow for a better understanding of the causes and progression of a person’s individual disease. More...
16 Jan 2020

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New AI Model Identifies Women Facing Future Risk of Breast Cancer

 Researchers from the Karolinska Institute (Stockholm, Sweden) have developed a sophisticated type of artificial intelligence (AI) which can outperform existing models at predicting which women are at future risk of breast cancer. More...
07 Jan 2020
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Google AI System Beats Doctors in Detecting Breast Cancer

 A team of researchers from Google Health (Palo Alto, CA, USA) have developed an artificial intelligence (AI) model which can spot breast cancer in de-identified screening mammograms (where identifiable information has been removed) with greater accuracy, fewer false positives, and fewer false negatives than experts. This can find future applications wherein the model could support radiologists performing breast cancer screenings. More...
06 Jan 2020
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Global Immunochemistry Diagnostic Devices and Equipment Market to Reach USD 19.24 Billion by 2022

 The global immunochemistry diagnostic devices and equipment market was valued at about USD 16.7 billion in 2018 and is projected to grow at a CAGR of 3.6% to USD 19.24 billion in 2022. The market growth will be driven by an increase in the incidence of target diseases, such as viral infections, cardiovascular diseases, cancer or hormonal disorders worldwide, mainly due to poor lifestyle choices. More...
03 Jan 2020
Image: CT scans of the head (Photo courtesy of UC San Francisco)

AI Outperforms Radiologists in Detecting Tiny Brain Hemorrhages on CT Scans

 Scientists at UC San Francisco (San Francisco, CA, USA) and UC Berkeley (Berkeley, CA, USA) have developed an algorithm that performed better than two out of four expert radiologists in finding tiny brain hemorrhages in head scans. The algorithm could help doctors treat patients with traumatic brain injuries (TBI), strokes and aneurysms. More...
02 Jan 2020
Image: Ultrasound image of thyroid nodule (Photo courtesy of Sidney Kimmel Cancer Center -- Jefferson Health)

New Automated Machine Learning Model Uses Ultrasound to Improve Thyroid Cancer Diagnosis

 A new study by researchers from the Sidney Kimmel Cancer Center -- Jefferson Health (Philadelphia, PA, USA) has demonstrated that 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. More...
02 Jan 2020
Image: Researchers used AI to improve mammogram image interpretation (Photo courtesy of the Department of Energy’s Oak Ridge National Laboratory).

New AI Algorithm Predicts Which Breast Cancer Patients Can Benefit From Additional Therapy

 Researchers from the Case Western Reserve University (Cleveland, OH, USA) have developed a new artificial intelligence (AI) algorithm that could help better determine which patients diagnosed with the pre-malignant breast cancer (commonly referred to as stage 0) are likely to progress to invasive breast cancer and might benefit from additional therapy over and above surgery alone. More...
01 Jan 2020

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