Are we over-sharing our personal health data?


Increased use of electronic medical records can improve treatments and diagnoses for patients, but they're also vulnerable to large data breaches. Are we sharing too much of our personal health data? It's a question worth asking after massive breaches of our personal health data in recent years and reports that, even in low-tech settings like a hospital waiting room, privacy protocols are faulty. According to the health trade publicationHIPAA Journal,more hospitals and doctors' practices reported breaches in 2016 than in any other year since the U.S. Department of Health and Human Services' Office of Civil Rights, which collects data on leaks, started publishing breach summaries in 2009. Among the latest leaks: Bronx-Lebanon Hospital Center in New York City left patients' names, home addresses, medical and mental health diagnoses, addiction histories, HIV statuses and even sexual assault and domestic violence reports exposed online.


AAAI Conferences

From electron density and sequence to structure: Integrating protein. Abstract This paper presents a computational methodology for integrating techniques from protein image interpretation and protein sequence threading, applied to the problem of structure determination from experimental X-ray crystallographic electron density maps. In the proposed architecture, image interpretation of an electron density map produces candidate structural segments; threading is applied to evaluate these hypothesized segments and thus to constrain the set of possible image interpretations. We present the results of experiments designed to test the ability of the threading module to discriminate between correct and incorrect alignments of protein sequences onto structural The authors wish to thank Tony Chiverton, Peter Sibbald, Carroll Johnson, Laurence Leherte, Temple Smith, Jim White, Bob Rogers, Raman Nambudripad and Ljubomir Buturovic for their useful discussions and for their assistance in the development of the theory and practice of our algorithms. Funding for this research was provided by the Natural Science and Engineering Research Council of Canada. The threading code was developed at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology, in consortium with the BioMolecular Engineering Research Center of Boston University, sponsored by the National Science Foundation under grant DIR-9121548. Support for the Artificial Intelligence Laboratory's research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-91-J-4038. Support for the BioMolecular Engineering Research Center's research is provided in part by the National Institutes of Health under grant RR02275-05. The long-term goal of this research is to improve our ability to determine protein structures from crystallographic data, and to further our understanding of the underlying relationship between sequence and structure.

With phishing a primary threat, hospitals should invest in machine learning security


On May 12, the largest ransomware outbreak in history took place, targeting 300,000 machines in 150 countries, with the U.K.'s National Health Service (NHS) taking the brunt of the attack. In fact, 48 hospital trusts in the U.K. were targeted by the NSA cyber weapon-powered WannaCry ransomware, in addition to an unknown number of hospitals in the United States. Further, the Health Information Trust Alliance (HITRUST) reported that not just hospital machines were infected, but also medical devices from both Bayer and Siemens. By shutting down systems, communication channels and equipment, cybercriminals locked healthcare professionals out of their EHRs, forced them to cancel appointments and even turned away emergency patients. Unfortunately, this is just another example of the healthcare industry being targeted by increasingly sophisticated and frequent ransomware attacks.

Stop the privatization of health data


Wearable devices that track fitness are a rich source of real-time health data. Over the past year, technology titans including Google, Apple, Microsoft and IBM have been hiring leaders in biomedical research to bolster their efforts to change medicine. In September 2015, Tom Insel announced that he would quit his position as head of the US National Institute of Mental Health to join Google Life Sciences (now Verily). Three months later, Michael McConnell took a leave of absence from directing major cardiovascular research programmes at California's Stanford University to join him. And last month, Stephen Friend took a senior position with Apple.

FDA Chief: AI Holds 'Enormous Promise' for Tomorrow's Health Care


Digital health tools have and continue to radically change how care is delivered and provided, helping with early detection and cutting costs. Wearable devices, telemedicine and mobile apps already enable patients to be more proactive with their health, and help care providers better tailor individual care. "Artificial intelligence, particularly efforts to use machine learning . . . He spoke April 26 at the Health Datapalooza in Washington, D.C., organized by Academy Health. "We know that to support the widespread adoption of AI tools, we need patients and providers to understand the connection between decision-making in traditional health care settings and the use of these advanced technologies," Gottlieb said.