Tag: AI
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AI decodes brain tumor DNA during surgery
Kun-Hsing Yu and HMS colleagues used AI to rapidly determine a brain tumor’s molecular identity during surgery, propeling the development of precision oncology. The tool is CHARM (Cryosection Histopathology Assessment and Review Machine.) Currently, genetic sequencing takes days to weeks. Accurate molecular diagnosis during surgery can help a neurosurgeon decide how much brain tissue…
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AI detects diabetes from fatty tissue in chest x rays
Judy Wawira Gichoya and Emory colleagues have developed an AI model that detects warning signs for diabetes in x rays collected during routine exams. The signs were also detected in patients who do not meet elevated risk guidelines. Applying deep learning to images and electronic health record data, the model that successfully flagged elevated diabetes risk in a retrospective analysis, often years before patients were…
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AI-based device increases ademona detection during colonoscopy
MAGENTIQ-COLO is an AI based FDA cleared colonoscopy device which offers a significant increase in Adenoma Detection Rate. Current high rates of missed and undetected adenomas during colonoscopy means that even regularly screened patients are still at risk of developing colon cancer. A missed polyp can lead to interval cancer, which accounts for approximately 8%…
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Biosensor detects misfiled proteins in Parkinson’s and Alzheimer’s disease
Hatice Altug, Hilal Lashue, and EPFL colleagues have developed ImmunoSEIRA, an AI-enhanced, biosensing tool for the detection of misfolded proteins linked to Parkinson’s and Alzheimer’s disease. The researchers also claim that neural networks can quantify disease stage and progression. The technology holds promise for early detection, monitoring, and assessing treatment options. Protein misfolding has been…
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AI predicts pancreatic cancer
Harvard professor Chris Sander used clinical data from 6 million patients in Denmark’s national health system and 3 million in the U.S. VA system to train an AI model to predict the occurrence of pancreatic cancer within 3, 6, 12, and 36 months. This could allow wider screening for the aggressive disease, which is often…
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AI reconstructs viewed images
Yu Takagi, Shinji Nishimoto and Osaka University colleagues have published a study which demonstrates that AI can read brain scans and re-create largely realistic versions of images a person has seen. Future applications could include enabling communication of people with paralysis, recording dreams, and understanding animal perception, among others. Additional training was used on the existing text-to-image generative…
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Google AI detects tuberculosis
Google’s deep learning technology detected tuberculosis with similar accuracy to radiologists in a Radiology study. 165,174 chest radiographs from 22,284 patients in four countries were scanned. In detecting active tuberculosis, its sensitivity was higher (88 percent versus 75 percent) and its specificity was noninferior (79 percent versus 84 percent) compared to nine radiologists. Costs were…
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Neural Network assesses sleep patterns for passive Parkinson’s diagnosis
MIT’s Dina Katabi has developed a non-contact, neural network-based system to detect Parkinson’s disease while a person is sleeping. By assessing nocturnal breathing patterns, the series of algorithms detects, and tracks the progression of, the disease — every night, at home. A device in the bedroom emits radio signals, analyzes their reflections off the surrounding…
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AI catches breast cancer earlier, more often than traditional screening alone
The mammography screening paradigm has not changed since the 1960s. Breast screening AI company Vara, with Essen University and Memorial Sloan Kettering hospitals, published a study showing that radiologists assisted by AI are better able to screen for breast cancer. The hope is that AI systems could detect cancers that doctors miss, provide better care…
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AI detects COVID in chest x rays
DeepCOVID-XR is a Northwestern University developed algorithm that automatically detects the signs of COVID-19 on a basic X-ray of the lungs. The system is able to detect COVID-19 in X-rays 10 times faster than thoracic radiologists and 1% to 6% more accurately. The developers said the AI could be used to rapidly screen patients at…
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AI for (much) earlier breast cancer detection – Constance Lehman
Connie Lehman — Professor, Radiology, Harvard Medical School; Chief of Breast Imaging, radiology, Massachusetts General Hospital; Co-director of AVON Breast Center, Radiology, Massachusetts General Hospital; and Director, Breast Imaging Research Center, Radiology, Massachusetts General Hospital spoke at ApplySci’s recent conference at Harvard Medical School. Click to listen to her talk on using AI to discover breast cancer 5 years…
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Wearable Tech + Digital Health + Neurotech Boston
Join ApplySci at the 12th Wearable Tech + Digital Health + Neurotech Boston conference on November 14, 2019 at Harvard Medical School featuring talks by Brad Ringeisen, DARPA – Joe Wang, UCSD – Carlos Pena, FDA – George Church, Harvard – Diane Chan, MIT – Giovanni Traverso, Harvard | Brigham & Womens – Anupam Goel, UnitedHealthcare – Nathan Intrator,…