Browsing Category: AI

Machine learning tools predict heart failure

Declan O’Regan and MRC London Institute of Medical Sciences colleagues believe that AI can predict when pulmonary hypertension patients require more aggressive treatment to prevent death. In a recent study,  machine learning software automatically analyzed moving images of a patient’s heart, captured during an MRI. It then used  image processing to build a “virtual 3D heart”, […]

Sensors + robotics + AI for safer aging in place

IBM and rice University are developing MERA — a Waston enabled robot meant to help seniors age in place. The system comprises a Pepper robot  interface, Watson, and Rice’s CameraVitals project, which calculates vital signs by recording video of a person’s face.  Vitals are measured multiple times each day. Caregivers are informed if the the camera and/or accelerometer detect […]

AI speech, text, image, identity analysis for healthcare, self-driving cars

The Baidu and Nvidia developed Baidu Brain is a robot that simulates the human brain using advanced algorithms, computing power, and data analysis. It can be used for voice recognition and synthesis, image recognition, natural language processing, and user profiling. Potential healthcare uses include disease recognition, treatment tracking, and rehabilitation progress. Wearable Tech + Digital Health + NeuroTech Silicon Valley – […]

AI identifies cancer after doctor misdiagnosis, used to personalize care

IBM Watson detected a rare form of leukemia in a patient in Japan, after comparing genetic changes with a database of 20 million research papers. She had been misdiagnosed by doctors for months, and received the wrong treatment for her cancer type. Watson has created partnerships with 16 US health systems and imaging firms to identify cancer, diabetes and […]

Machine learning for faster stroke diagnosis

MedyMatch uses big data and artificial intelligence to improve stroke diagnosis, with the goal of faster treatment. Patient CT photos are scanned  and immediately compared with hundreds of thousands of other patient results.  Almost any deviation from a normal CT is quickly detected. With current methods, medical imaging errors can occur when emergency room radiologists […]

Machine learning analysis of doctor notes predicts cancer progression

Gunnar Rätsch and Memorial Sloan Kettering colleagues are using AI to find similarities between cancer cases.  Ratsch’s algorithm has analyzed 100 million sentences taken from clinical notes of about 200,000 cancer patients to predict disease progression. In a recent study, machine learning was used to classify  patient symptoms, medical histories and doctors’ observations into 10,000 clusters. Each […]

Brain architecture linked to consciousness, abstract thought

UMass professor Hava Siegelmann used fMRI data from tens of thousands of patients to understand how thought arises from brain structure. This resulted in a geometry-based  method meant to advance the identification and treatment of brain disease.  It can also be used to improve deep learning systems, and her lab is now creating a “massively recurrent deep learning […]