Emergence of teleradiology, PACS, and other radiology IT solutions in Acta Radiologica.

For this historical review, we searched a database containing all the articles published in Acta Radiologica during its 100-year history to find those on the use of information technology (IT) in radiology. After reading the full texts, we selected the presented articles according to major radiology IT domains such as teleradiology, picture archiving and communication systems, image processing, image analysis, and computer-aided diagnostics in order to describe the development as it appeared in the journal. Publications generally follow IT megatrends, but because the contents of Acta Radiologica are mainly clinically oriented, some technology achievements appear later than they do in journals discussing mainly imaging informatics topics.

Evidence-based pathology in its second decade: toward probabilistic cognitive computing.

Evidence-based pathology advocates using a combination of best available data ("evidence") from the literature and personal experience for the diagnosis, estimation of prognosis, and assessment of other variables that impact individual patient care. Evidence-based pathology relies on systematic reviews of the literature, evaluation of the quality of evidence as categorized by evidence levels and statistical tools such as meta-analyses, estimates of probabilities and odds, and others. However, it is well known that previously "statistically significant" information usually does not accurately forecast the future for individual patients. There is great interest in "cognitive computing" in which "data mining" is combined with "predictive analytics" designed to forecast future events and estimate the strength of those predictions. This study demonstrates the use of IBM Watson Analytics software to evaluate and predict the prognosis of 101 patients with typical and atypical pulmonary carcinoid tumors in which Ki-67 indices have been determined. The results obtained with this system are compared with those previously reported using "routine" statistical software and the help of a professional statistician. IBM Watson Analytics interactively provides statistical results that are comparable to those obtained with routine statistical tools but much more rapidly, with considerably less effort and with interactive graphics that are intuitively easy to apply. It also enables analysis of natural language variables and yields detailed survival predictions for patient subgroups selected by the user. Potential applications of this tool and basic concepts of cognitive computing are discussed.

Artificial intelligence in healthcare: past, present and future.

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.

Ambulatory electrocardiology.

About 50 years ago, Norman Jefferis Holter invented a device that opened the possibility of recording heart activity over long periods of time. This invention, together with the rapid developments in electronics, has enabled a revolutionary change in the diagnosis and management of cardiac diseases. Ambulatory cardiac monitors have decreased in size to the point of becoming wearable or implantable and are able to monitor heart activity for months or even years. In addition, new telecommunication systems allow clinicians to remotely access cardiac events and to respond within a short period of time. Novel advances in computing and algorithm development are expanding the clinical applications of ambulatory devices with more complex automatic interpretation of the electrocardiographic signal. This article reviews the state of the art of these techniques from both clinical and technical approaches, covering a historic perspective up to today, and discusses current applications, challenges, and future directions.

History and structures of telecommunication in pathology, focusing on open access platforms.

BACKGROUND: Telecommunication has matured to a broadly applied tool in diagnostic pathology. TECHNOLOGY AND SYSTEMS: Contemporary with the development of fast electronic communication lines (Integrated digital network services (ISDN), broad band connections, and fibre optics, as well as the digital imaging technology (digital camera), telecommunication in tissue--based diagnosis (telepathology) has matured. Open access (internet) and server--based communication have induced the development of specific medical information platforms, such as iPATH, UICC-TPCC (telepathology consultation centre of the Union International against Cancer), or the Armed Forces Institute of Pathology (AFIP) teleconsultation system. They have been closed, and are subject to be replaced by specific open access forums (Medical Electronic Expert Communication System (MECES) with embedded virtual slide (VS) technology). MECES uses php language, data base driven mySqL architecture, X/L-AMPP infrastructure, and browser friendly W3C conform standards. EXPERIENCES: The server--based medical communication systems (AFIP, iPATH, UICC-TPCC) have been reported to be a useful and easy to handle tool for expert consultation. Correct sampling and evaluation of transmitted still images by experts reported revealed no or only minor differences to the original images and good practice of the involved experts. ß tests with the new generation medical expert consultation systems (MECES) revealed superior results in terms of performance, still image viewing, and system handling, especially as this is closely related to the use of so--called social forums (facebook, youtube, etc.). BENEFITS AND EXPECTATIONS: In addition to the acknowledged advantages of the former established systems (assistance of pathologists working in developing countries, diagnosis confirmation, international information exchange, etc.), the new generation offers additional benefits such as acoustic information transfer, assistance in image screening, VS technology, and teaching in diagnostic sampling, judgement, and verification.

A history of the INTERNIST-1 and Quick Medical Reference (QMR) computer-assisted diagnosis projects, with lessons learned.

The INTERNIST-1/Quick Medical Reference (QMR) diagnostic decision support project spans four decades, from 1971-onward. This paper describes the history of the project and details insights gained of relevance to the general clinical and informatics communities.

Computer-assisted diagnostic decision support: history, challenges, and possible paths forward.

This paper presents a brief history of computer-assisted diagnosis, including challenges and future directions. Some ideas presented in this article on computer-assisted diagnostic decision support systems (CDDSS) derive from prior work by the author and his colleagues (see list in Acknowledgments) on the INTERNIST-1 and QMR projects. References indicate the original sources of many of these ideas.

Prinzmetal's work and the "Sclarovsky-Birnbaum ischemia score" for acute myocardial infarction: a parallel in systematizing electrocardiographic knowledge.

In this viewpoint, the author traces back in time the original (? if possible) description of the electrocardiographic hallmarks of myocardial ischemic injury leading to myocardial infarction. In this venture, he detects a parallel between the work of Prinzmetal et al and that of Sclarovsky and Birnbaum and al, in their approach to research, which is based on systemization and utilization of electrocardiographic knowledge.

Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. In this article, the motivation and philosophy for early development of CAD schemes are presented together with the current status and future potential of CAD in a PACS environment. With CAD, radiologists use the computer output as a "second opinion" and make the final decisions. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral chest images has the potential to improve the overall performance in the detection of lung nodules when combined with another CAD scheme for PA chest images. Because vertebral fractures can be detected reliably by computer on lateral chest radiographs, radiologists' accuracy in the detection of vertebral fractures would be improved by the use of CAD, and thus early diagnosis of osteoporosis would become possible. In MRA, a CAD system has been developed for assisting radiologists in the detection of intracranial aneurysms. On successive bone scan images, a CAD scheme for detection of interval changes has been developed by use of temporal subtraction images. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for chest CAD may include the computerized detection of lung nodules, interstitial opacities, cardiomegaly, vertebral fractures, and interval changes in chest radiographs as well as the computerized classification of benign and malignant nodules and the differential diagnosis of interstitial lung diseases. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with known pathology, which would be very similar to a new unknown case, from PACS when a reliable and useful method has been developed for quantifying the similarity of a pair of images for visual comparison by radiologists.

ANAM genogram: historical perspectives, description, and current endeavors.

This paper presents a historical overview and current perspective of the Automated Neuropsychological Assessment Metrics (ANAM) test system. We discuss the history of its development along with a synopsis of the evolution of computerized testing that has occurred and led to ANAM over the past 30 years within the Department of Defense (DoD). We include a description of our current system and test library. Finally, we present an overview of advanced development projects that are presently underway. We have intentionally avoided addressing issues of reliability, stability, clinical sensitivity, and construct validity in this paper. These issues are presented in other reports in this special issue.

Fifty years in medical informatics.

OBJECTIVES: An overview of personal experiences in medical informatics based on Dr. Morris Collen's 50 years of research in the field. METHODS: A personal reminiscence and historical overview, focusing on the first two decades of medical informatics, when Dr. Collen began working with Dr. Sidney Garfield, the founder of Kaiser Permanente, leading to his involvement in computer-based medical care, through the development of the pioneering Automated Multiphasic Health Testing (AMHT) system, which they introduced into Kaiser clinics in Oakland and San Francisco. RESULTS: Statistical models for medical decision-making based on consultations with Jerzy Neyman and George Dantzig were incorporated into the AMHT, and tested on a large database of cases. Meetings with other pioneers in medical informatics at the Karolinska Institute led to the formation of the early society Salutas Unitas, and the many national and international collaborations which followed during the first two decades helped coalesce the field as clinicians and researchers investigated problems of medical data, decision support, and laboratory, hospital, and library information systems. CONCLUSION: Dr. Collen's research and his many medical informatics activities significantly contributed to the growth of the field. The U.S. contributions are covered extensively in his book, A History of Medical Informatics in the United States, 1950-1990. Washington, DC: Am Med Informatics Association 1995.

Computers in clinical assessment: historical developments, present status, and future challenges.

Computerized testing methods have long been regarded as a potentially powerful asset for providing psychological assessment services. Ever since computers were first introduced and adapted to the field of assessment psychology in the 1950s, they have been a valuable aid for scoring, data processing, and even interpretation of test results. The history and status of computer-based personality and neuropsychological tests are discussed in this article. Several pertinent issues involved in providing test interpretation by computer are highlighted. Advances in computer-based test use, such as computerized adaptive testing, are described and problems noted. Today, there is great interest in expanding the availability of psychological assessment applications on the Internet. Although these applications show great promise, there are a number of problems associated with providing psychological tests on the Internet that need to be addressed by psychologists before the Internet can become a major medium for psychological service delivery.