Browsing Category: AI

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 […]

AI/EMG system improves prosthetic hand control

UT Dallas researchers Mohsen Jafarzadeh, Yonas Tadesse, and colleagues are using AI to control prosthetic hands with raw EMG signals. The real-time convolutional neural network, which does not require preprocessing, results in faster and more accurate data classification and faster hand movements. User data re-trains the system to personalize actions. Join ApplySci at the 12th Wearable Tech […]

AIgorithm detects cancer potential of pancreatic cysts

CompCyst is a proof-of-concept study, led by Anne Marie Lennon at Johns Hopkins, which uses AI to more accurately determine which pancreatic cysts will become cancerous. The test evaluates molecular and clinical markers in cyst fluids, and could significantly improve detection rates vs. current clinical and imaging tests. In the study, the researchers evaluated molecular profiles, […]

Study: AI accurately predicts childhood disease from health records

Xia Huimin and Guangzhou Women and Children’s Medical Center researchers used AI to read 1.36 million pediatric health records, and diagnosed disease as accurately as doctors, according to a recent study. Common childhood diseases were detected after processing symptoms, medical history and other clinical data from this massive sample.  The goal is the diagnosis of complex […]

AI predicts response to antipsychotic drugs, could distinguish between disorders

Lawson Health Research Institute, Mind Research Network and Brainnetome Center researchers have developed an algorithm that analyzes brain scans to classify illness in patients with complex mood disorders and help predict their response to medication. A recent study analyzed and compared fMRI scans of those with MDD, bipolar I,  and no history of mental illness, and […]

AI speeds MRI scans

Facebook and NYU’s fastMRI project, led by Larry Zitnick, uses AI in an attempt to make MRI imaging 10 times faster. Neural networks will be trained to fill in missing or degraded parts of scans, turning them from low resolution into high. The goal is to significantly reduce the time patients must lie motionless inside an […]