Web: http://arxiv.org/abs/2209.06528

Sept. 15, 2022, 1:11 a.m. | Flavio Di Martino, Franca Delmastro

cs.LG updates on arXiv.org arxiv.org

Nowadays Artificial Intelligence (AI) has become a fundamental component of
healthcare applications, both clinical and remote, but the best performing AI
systems are often too complex to be self-explaining. Explainable AI (XAI)
techniques are defined to unveil the reasoning behind the system's predictions
and decisions, and they become even more critical when dealing with sensitive
and personal health data. It is worth noting that XAI has not gathered the same
attention across different research areas and data types, especially in …

applications arxiv data explainable ai health remote series survey tabular time series

More from arxiv.org / cs.LG updates on arXiv.org

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Data Scientist (Analytics) - Singapore

@ Momos | Singapore, Central, Singapore

Machine Learning Scientist, Drug Discovery

@ Flagship Pioneering, Inc. | Cambridge, MA

Applied Scientist - Computer Vision

@ Flawless | Los Angeles, California, United States

Sr. Data Engineer, Customer Service

@ Wayfair Inc. | Boston, MA