Use of a Novel Imaging Technology for Remote Autism Diagnosis: A Reflection on Experience of Stakeholders

AbstractTimely diagnosis and early interventions are critical to improving the long term functioning of a child with ASD. However, a major challenge facing parents is difficulty in obtaining on-time access to appropriate diagnostic services. To address this need, an imaging technology, NODA® (Naturalistic Observation Diagnostic Assessment), has been successfully developed and field-tested. NODA® includes 1) NODA SmartCapture; a smart-phone based recording system for parents to capture and share in-home video evidence of their child behavior and 2) NODA Connect; a HIPPA compliant web-platform for diagnosticians to conduct remote autism diagnostic assessments based on in-home video evidence of behavior, developmental history and their clinical judgment. In the field study, parents captured and shared videos evidence from their homes via NODA SmartCapture and diagnosticians conducted remote diagnostic assessment via NODA Connect. Results show that parents were able to successfully collect video evidence of behavior as per given prescription and diagnosticians were able to complete remote diagnostic assessments. This paper is a reflection on the first hand experience of key stakeholders (parents and diagnosticians) using NODA® in the field

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic “cognitive” functions that we associate with our mind, such as “learning” and “solving problem”. New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors