“A pop-up would appear, asking about a patient’s level of pain. Then, a drop-down menu would list treatments ranging from a referral to a pain specialist to a prescription for an opioid painkiller. Click a button, and the program would create a treatment plan. From 2016 to spring 2019, the alert went off about 230 million times. The tool existed thanks to a secret deal. Its maker, a software company called Practice Fusion, was paid by a major opioid manufacturer to design it in an effort to boost prescriptions for addictive pain pills — even though overdose deaths had almost tripled during the previous 15 years, creating a public-health disaster. The software was used by tens of thousands of doctors’ offices.”
Source : In secret deal with drugmaker, health-records tool pushed opioids – Los Angeles Times
“The data shared included:
- drug names entered into Drugs.com were sent to Google’s ad unit DoubleClick.
- symptoms inputted into WebMD’s symptom checker, and diagnoses received, including “drug overdose”, were shared with Facebook.
- menstrual and ovulation cycle information from BabyCentre ended up with Amazon Marketing, among others.
- keywords such as “heart disease” and “considering abortion” were shared from sites like the British Heart Foundation, Bupa and Healthline to companies including Scorecard Research and Blue Kai (owned by software giant Oracle).
In eight cases (with the exception of Healthline and Mind), a specific identifier linked to the web browser was also transmitted — potentially allowing the information to be tied to an individual — and tracker cookies were dropped before consent was given. Healthline confirmed that it also shared unique identifiers with third parties.
None of the websites tested asked for this type of explicit and detailed consent.”
Source : How top health websites are sharing sensitive data with advertisers | Financial Times
“Le CHU a, en tout cas, fortement pâti de cet épisode. Tout le système informatique a dû être arrêté, et le personnel est repassé « à la bonne vieille méthode du papier et du crayon », selon les propos de Rémi Heym, directeur de la communication du CHU, recueillis par l’Agence France-Presse. « Cela a entraîné des délais très longs de prise en charge, même s’il n’y a pas eu de mise en péril de la santé des personnes hospitalisées. » Depuis l’épisode du rançongiciel WannaCry en 2017, les hôpitaux français, et plus largement le secteur de la santé, inquiètent les autorités spécialisées. Les établissements de santé conjuguent en effet un triple facteur de risque : des moyens parfois limités consacrés à la sécurité informatique ; des données extrêmement précieuses, dont les pirates savent qu’ils peuvent exiger le prix fort pour en restaurer l’accès ; et de nombreux appareils médicaux, de plus en plus connectés et pas forcément sécurisés.”
Source : Attaque informatique au CHU de Rouen : une enquête ouverte
“Neither patients nor doctors have been notified. At least 150 Google employees already have access to much of the data on tens of millions of patients, according to a person familiar with the matter and the documents. In a news release issued after The Wall Street Journal reported on Project Nightingale on Monday, the companies said the initiative is compliant with federal health law and includes robust protections for patient data. Some Ascension employees have raised questions about the way the data is being collected and shared, both from a technological and ethical perspective, according to the people familiar with the project. But privacy experts said it appeared to be permissible under federal law. That law, the Health Insurance Portability and Accountability Act of 1996, generally allows hospitals to share data with business partners without telling patients, as long as the information is used “only to help the covered entity carry out its health care functions.””
Source : Google’s ‘Project Nightingale’ Gathers Personal Health Data on Millions of Americans – WSJ
“Yisroel Mirsky, Yuval Elovici and two others at the Ben-Gurion University Cyber Security Research Center in Israel who created the malware say that attackers could target a presidential candidate or other politicians to trick them into believing they have a serious illness and cause them to withdraw from a race to seek treatment. The research isn’t theoretical. In a blind study the researchers conducted involving real CT lung scans, 70 of which were altered by their malware, they were able to trick three skilled radiologists into misdiagnosing conditions nearly every time. In the case of scans with fabricated cancerous nodules, the radiologists diagnosed cancer 99 percent of the time. In cases where the malware removed real cancerous nodules from scans, the radiologists said those patients were healthy 94 percent of the time.”
Source : Hospital viruses: Fake cancerous nodes in CT scans, created by malware, trick radiologists – The Washington Post
“Le tribunal a retenu contre lui une amende de 443 000 dollars et 10 ans de prison selon Reuters. Gottesfled fera appel même s’il ne regrette en rien ses actions et se confronte à la dure loi CFAA inventée sous l’ère Reagan, protégeant les systèmes informatiques publics jusqu’à l’excès. Le procureur d’Addio estime que Gottesfled a mis en danger la vie des enfants tout en qualifiant l’accusé d’ « autoglorifier » la menace qu’il représentait. Justina Pelletier, depuis sortie d’internement, prend aujourd’hui la parole pour défendre Gottesfled, « il ne devrait pas être en prison » juge-t-elle auprès de Rolling Stone. Aujourd’hui, après avoir largement contribué à faire connaître le mot-dièse #justice4justina, Martin Gottesfled donne naissance malgré lui à celui de #FreeMartyG. Un concentré d’Amérique, à l’heure d’Internet.”
Source : Martin Gottesfled, le hackeur qui voulait « sauver les enfants », reste en prison – Cyberguerre
“Google has been accused of breaking promises to patients, after the company announced it would be moving a healthcare-focused subsidiary, DeepMind Health, into the main arm of the organisation.The restructure, critics argue, breaks a pledge DeepMind made when it started working with the NHS that “data will never be connected to Google accounts or services”. The change has also resulted in the dismantling of an independent review board, created to oversee the company’s work with the healthcare sector, with Google arguing that the board was too focused on Britain to provide effective oversight for a newly global body.”
Source : Google ‘betrays patient trust’ with DeepMind Health move | Technology | The Guardian
“A startup founded in Palo Alto, California, by a trio of doctors, including the former director of the US National Institute of Mental Health, is trying to prove that our obsession with the technology in our pockets can help treat some of today’s most intractable medical problems: depression, schizophrenia, bipolar disorder, post-traumatic stress disorder, and substance abuse. Mindstrong Health is using a smartphone app to collect measures of people’s cognition and emotional health as indicated by how they use their phones. Once a patient installs Mindstrong’s app, it monitors things like the way the person types, taps, and scrolls while using other apps. This data is encrypted and analyzed remotely using machine learning, and the results are shared with the patient and the patient’s medical provider.”
Source : The smartphone app that can tell you’re depressed before you know it yourself – MIT Technology Review
“In both datasets, LYNA was able to correctly distinguish a slide with metastatic cancer from a slide without cancer 99% of the time. Further, LYNA was able to accurately pinpoint the location of both cancers and other suspicious regions within each slide, some of which were too small to be consistently detected by pathologists. As such, we reasoned that one potential benefit of LYNA could be to highlight these areas of concern for pathologists to review and determine the final diagnosis.”
Source : Google AI Blog: Applying Deep Learning to Metastatic Breast Cancer Detection
“We don’t just want this to be an academically interesting result – we want it to be used in real treatment. So our paper also takes on one of the key barriers for AI in clinical practice: the “black box” problem. For most AI systems, it’s very hard to understand exactly why they make a recommendation. That’s a huge issue for clinicians and patients who need to understand the system’s reasoning, not just its output – the why as well as the what.
Our system takes a novel approach to this problem, combining two different neural networks with an easily interpretable representation between them. The first neural network, known as the segmentation network, analyses the OCT scan to provide a map of the different types of eye tissue and the features of disease it sees, such as haemorrhages, lesions, irregular fluid or other symptoms of eye disease. This map allows eyecare professionals to gain insight into the system’s “thinking.” The second network, known as the classification network, analyses this map to present clinicians with diagnoses and a referral recommendation. Crucially, the network expresses this recommendation as a percentage, allowing clinicians to assess the system’s confidence in its analysis”.
Source : A major milestone for the treatment of eye disease | DeepMind