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Explain yourself, machine. Producing simple text descriptions for AI interpretability
We describe a feature, give a location, and then synthesise a conclusion. For example: There is an irregular mass with microcalcification in the upper outer quadrant of the breast. Findings are consistent with malignancy. You don’t need to understand the words I used here, but the point is that the features (irregular mass, microcalcification) are consistent with the diagnosis (breast cancer, malignancy). A doctor reading this report already sees internal consistency, and that reassures them that the report isn’t wrong. An common example of a wrong report could be: Irregular mass or microcalcification. No ...
Source: The Health Care Blog - December 12, 2019 Category: Consumer Health News Authors: Christina Liu Tags: Artificial Intelligence Health Tech AI Luke Oakden-Rayner machine learning Radiology Source Type: blogs

The Future of Emergency Medicine: Innovations Making Patients The Point-of-Care
Every minute spent without treatment could reduce the chance of survival in case of medical emergency and trauma patients. Digital health innovations making patients the point-of-care could become a great help for first responders and emergency units in the battle against time. Here, we collected what trends and technologies will have an impact on the future of emergency medicine. Six minutes before brain damage Car crashes, home injuries, fires, natural disasters. The difference between life and death often depends on the speed and efficiency of emergency care services. The work of doctors, paramedics, and nurses being in...
Source: The Medical Futurist - November 28, 2017 Category: Information Technology Authors: nora Tags: imported CPR digital health emergency emergency medicine EMS first aid first response future Health 2.0 Healthcare Innovation technology Source Type: blogs