Artificial intelligence (AI) research within medicine is growing rapidly. In 2016, healthcare AI projects attracted more investment than AI projects within any other sector of the global economy.1 However, among the excitement, there is equal scepticism, with some urging caution at inflated expectations.2 This article takes a close look at current trends in medical AI and the future possibilities for general practice.
 

The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Although there are many instances in which AI can perform healthcare tasks as well or better than humans, implementation factors will prevent large-scale automation of healthcare professional jobs for a considerable period. Ethical issues in the application of AI to healthcare are also discussed.   
 

Artificial intelligence (AI) has the potential to ease the human resources crisis in healthcare by facilitating diagnostics, decision-making, big data analytics and administration, among others. For this we must first tackle the technological, ethical and legal obstacles. The human resource crisis is widening worldwide, and it is obvious that it is not possible to provide care without workforce. How can disruptive technologies in healthcare help solve the variety of human resource problems? Will technology empower physicians or replace them? How can the medical curriculum, including post-graduate education prepare professionals for the meaningful use of technology? These questions have been growing for decades, and the promise of disruptive technologies filling them is imminent with digital health becoming widespread. Authors of this essay argue that AI might not only fill the human resources gap, but also raises ethical questions we need to deal with today. While there are even more questions to address, our stand is that AI is not meant to replace caregivers, but those who use AI will probably replace those who don’t. And it is possible to prepare for that. 

Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.
 

The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.
 

Policymakers and practitioners show a continued interest in telehealth’s potential to increase efficiency and reach patients facing access barriers. However, telehealth encompasses many applications for varied conditions and populations. It is therefore difficult to draw broad conclusions about telehealth’s efficacy. This rapid review examines recent evidence both about telehealth’s efficacy by clinical area and about telehealth’s impact on utilization. We searched for systematic reviews and meta-analyses of the use of telehealth services by patients of any age for any condition published in English in the period January 2004–May 2018. Twenty systematic reviews and associated meta-analyses are included in this review, covering clinical areas such as mental health and rehabilitation. Broadly, telehealth interventions appear generally equivalent to in-person care. However, telehealth’s impact on the use of other services is unclear. Many factors should be carefully considered when weighing the evidence of telehealth’s efficacy, including modality, evidence quality, population demographics, and point-in-time measurement of outcomes. 

Final Report: Strategy on Reducing Regulatory and Administrative Burden Relating to the Use of Health IT and EHRs

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What would a better health care system for all Americans be like? This is the question that the American College of Physicians (ACP) has been asking of its members since July 2018, when the ACP Board of Regents asked ACP's Health and Public Policy Committee and Medical Practice and Quality Committee to “develop a new vision for the future of health care policy,” to examine ways to achieve universal coverage with improved access to care, reduce per capita health care costs and the rate of growth in spending, reform clinician compensation, and reduce the complexity of our health care system.

To develop this vision and recommend ways to realize it, ACP considered evidence on the effectiveness of health care in the United States and other countries; solicited input from U.S-based members and ACP's policy committees; adopted draft recommendations for review by ACP's regents, governors, committees, and council members; finalized recommendations in response to this feedback; and submitted the recommendations for approval by the ACP Board of Regents. On 2 November 2019, the Board of Regents approved this call to action and 3 companion papers on coverage and cost of care (1), health care delivery and payment system reforms (2), and reducing barriers to care and addressing social determinants of health (3).
 

The American College of Physicians (ACP) has long advocated for universal access to high-quality health care in the United States. Yet, it Is essential that the U.S.health system goes beyond ensuring coverage, efficient delivery systems, and affordability. Fundamental restructuring of payment policies and delivery systems is required to achieve a health care system that puts patients' interests first and supports physicians and their care teams to deliver high-value,patient-and family-centered care.ACP calls for reform of U.S. payment, delivery, and information technology systems to achieve this vision. The ACP's recommendations include increased investment in primary care; alignment of financial incentives to achieve better patient outcomes, lower costs, reduce inequities in health care, and facilitate team-based care; freeing patients and physicians of inefficient administrative and billing tasks and documentation requirements; and development of health information technologies that enhance the patient-physician relationship.

The California Consumer Privacy Act (CCPA) is set to begin implementation in 2020. It is the strictest privacy legislation in the country, granting California residents significantly more control over their personal information. Are you prepared to comply?