The term Artificial Intelligence (AI) was coined by John McCarthy in 1956 during a conference held on this subject. However, the possibility of machines being able to simulate human behavior and actually think was raised earlier by Alan Turing who developed the Turing test in order to differentiate humans from machines. Since then, computational power has grown to the point of instant calculations and the ability evaluate new data, according to previously assessed data, in real time. Today, AI is integrated into our daily lives in many forms, such as personal assistants (Siri, Alexa, Google assistant etc.), automated mass transportation, aviation and computer gaming. More recently, AI has also begun to be incorporated into medicine to improve patient care by speeding up processes and achieving greater accuracy, opening the path to providing better healthcare overall. Radiological images, pathology slides, and patients' electronic medical records (EMR) are being evaluated by machine learning, aiding in the process of diagnosis and treatment of patients and augmenting physicians' capabilities. Herein we describe the current status of AI in medicine, the way it is used in the different disciplines and future trends.

Introduction to artificial intelligence in medicine.

Surgical data science – from concepts toward clinical translation

Surgical Data Science - from Concepts toward Clinical Translation

The new medical device communication protocol known as IEEE 11073 SDC is well-suited for the integration of (surgical) point-of-care devices, so are the established Health Level Seven (HL7) V2 and Digital Imaging and Communications in Medicine (DICOM) standards for the communication of systems in the clinical IT infrastructure (CITI). An integrated operating room (OR) and other integrated clinical environments, however, need interoperability between both domains to fully unfold their potential for improving the quality of care as well as clinical workflows. This work thus presents concepts for the propagation of clinical and administrative data to medical devices, physiologic measurements and device parameters to clinical IT systems, as well as image and multimedia content in both directions. Prototypical implementations of the derived components have proven to integrate well with systems of networked medical devices and with the CITI, effectively connecting these heterogeneous domains. Our qualitative evaluation indicates that the interoperability concepts are suitable to be integrated into clinical workflows and are expected to benefit patients and clinicians alike. The upcoming HL7 Fast Healthcare Interoperability Resources (FHIR) communication standard will likely change the domain of clinical IT significantly. A straightforward mapping to its resource model thus ensures the tenability of these concepts despite a foreseeable change in demand and requirements.

Connecting the clinical IT infrastructure to a service-oriented architecture of medical devices.

Interoperability of medical devices based on standards starts to establish in the operating room (OR). Devices share their data and control functionalities. Yet, the OR technology rarely implements cooperative, intelligent behavior, especially in terms of active cooperation with the OR team. Technical context-awareness will be an essential feature of the next generation of medical devices to address the increasing demands to clinicians in information seeking, decision making, and human–machine interaction in complex surgical working environments. The paper describes the technical validation of an intelligent surgical working environment for endoscopic ear–nose–throat surgery. We briefly summarize the design of our framework for context-aware system’s behavior in integrated OR and present example realizations of novel assistance functionalities. In a study on patient phantoms, twenty-four procedures were implemented in the proposed intelligent surgical working environment based on recordings of real interventions. Subsequently, the whole processing pipeline for context-awareness from workflow recognition to the final system’s behavior is analyzed. Rule-based behavior that considers multiple perspectives on the procedure can partially compensate recognition errors. A considerable robustness could be achieved with a reasonable quality of the recognition. Overall, reliable reactive as well as proactive behavior of the surgical working environment can be implemented in the proposed environment. The obtained validation results indicate the suitability of the overall approach. The setup is a reliable starting point for a subsequent evaluation of the proposed context-aware assistance. The major challenge for future work will be to implement the complex approach in a cross-vendor setting.

The intelligent OR: design and validation of a context-aware surgical working environment.

Clinical working environments have become very complex imposing many different tasks in diagnosis, medical treatment, and care procedures. During the German flagship project OR.NET, more than 50 partners developed technologies for an open integration of medical devices and IT systems in the operating room. The aim of the present work was to evaluate a large set of the proposed concepts from the perspectives of various stakeholders. The demonstration OR is focused on interventions from the head and neck surgery and was developed in close cooperation with surgeons and numerous colleagues of the project partners. The demonstration OR was qualitatively evaluated including technical as well as clinical aspects. In the evaluation, a questionnaire was used to obtain feedback from hospital operators. The clinical implications were covered by structured interviews with surgeons, anesthesiologists and OR staff. In the present work, we qualitatively evaluate a subset of the proposed concepts from the perspectives of various stakeholders. The feedback of the clinicians indicates that there is a need for a flexible data and control integration. The hospital operators stress the need for tools to simplify risk management in openly integrated operating rooms. The implementation of openly integrated operating rooms will positively affect the surgeons, the anesthesiologists, the surgical nursing staff, as well as the technical personnel and the hospital operators. The evaluation demonstrated the need for OR integration technologies and identified the missing tools to support risk management and approval as the main barriers for future installments.

OR.NET: multi-perspective qualitative evaluation of an integrated operating room based on IEEE 11073 SDC

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OR.NET: multi-perspective qualitative evaluation of an integrated operating room based on IEEE 11073 SDC