Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view

Digital pathology (DP) is increasingly entering routine clinical pathology diagnostics. As digitization of the routine caseload advances, implementation of digital image analysis algorithms and artificial intelligence tools becomes not only attainable, but also desirable in daily sign out. The Swiss Digital Pathology Consortium (SDiPath) has initiated a Delphi process to generate best-practice recommendations for various phases of the process of digitization in pathology for the local Swiss environment, encompassing the following four topics: i) scanners, quality assurance, and validation of scans; ii) integration of scanners and systems into the pathology laboratory information system; iii) the digital workflow; and iv) digital image analysis (DIA)/artificial intelligence (AI). The current article focuses on the DIA-/AI-related recommendations generated and agreed upon by the working group and further verified by the Delphi process among the members of SDiPath. Importantly, they include the view and the currently perceived needs of practicing pathologists from multiple academic and cantonal hospitals as well as private practices

Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology

Integration of digital pathology (DP) into clinical diagnostic workflows is increasingly receiving attention as new hardware and software become available. To facilitate the adoption of DP, the Swiss Digital Pathology Consortium (SDiPath) organized a Delphi process to produce a series of recommendations for DP integration within Swiss clinical environments. This process saw the creation of 4 working groups, focusing on the various components of a DP system (1) scanners, quality assurance and validation of scans, (2) integration of Whole Slide Image (WSI)-scanners and DP systems into the Pathology Laboratory Information System, (3) digital workflow-compliance with general quality guidelines, and (4) image analysis (IA)/artificial intelligence (AI), with topic experts for each recruited for discussion and statement generation. The work product of the Delphi process is 83 consensus statements presented here, forming the basis for "SDiPath Recommendations for Digital Pathology". They represent an up-to-date resource for national and international hospitals, researchers, device manufacturers, algorithm developers, and all supporting fields, with the intent of providing expectations and best practices to help ensure safe and efficient DP usage

The utilisation of health research in policy-making: Concepts, examples and methods of assessment

The importance of health research utilisation in policy-making, and of understanding the mechanisms involved, is increasingly recognised. Recent reports calling for more resources to improve health in developing countries, and global pressures for accountability, draw greater attention to research-informed policy-making. Key utilisation issues have been described for at least twenty years, but the growing focus on health research systems creates additional dimensions. The utilisation of health research in policy-making should contribute to policies that may eventually lead to desired outcomes, including health gains. In this article, exploration of these issues is combined with a review of various forms of policy-making. When this is linked to analysis of different types of health research, it assists in building a comprehensive account of the diverse meanings of research utilisation. Previous studies report methods and conceptual frameworks that have been applied, if with varying degrees of success, to record utilisation in policy-making. These studies reveal various examples of research impact within a general picture of underutilisation. Factors potentially enhancing utilisation can be identified by exploration of: priority setting; activities of the health research system at the interface between research and policy-making; and the role of the recipients, or 'receptors', of health research. An interfaces and receptors model provides a framework for analysis. Recommendations about possible methods for assessing health research utilisation follow identification of the purposes of such assessments. Our conclusion is that research utilisation can be better understood, and enhanced, by developing assessment methods informed by conceptual analysis and review of previous studies

Initial experience with AI Pathway Companion: Evaluation of dashboard-enhanced clinical decision making in prostate cancer screening.

PurposeRising complexity of patients and the consideration of heterogeneous information from various IT systems challenge the decision-making process of urological oncologists. Siemens AI Pathway Companion is a decision support tool that provides physicians with comprehensive patient information from various systems. In the present study, we examined the impact of providing organized patient information in comprehensive dashboards on information quality, effectiveness, and satisfaction of physicians in the clinical decision-making process.MethodsTen urologists in our department performed the entire diagnostic workup to treatment decision for 10 patients in the prostate cancer screening setting. Expenditure of time, information quality, and user satisfaction during the decision-making process with AI Pathway Companion were recorded and compared to the current workflow.ResultsA significant reduction in the physician's expenditure of time for the decision-making process by -59.9% (p ConclusionThe software demonstrated that comprehensive organization of information improves physician's effectiveness and satisfaction in the clinical decision-making process. Further development is needed to map more complex patient pathways, such as the follow-up treatment of prostate cancer

Knowde: A Visual Search Interface

Information Visualizations are well-established to represent high density information in an intuitive and interactive way. There are no popular general retrieval systems, however, which utilize the power of information visualizations for search result representation. This paper describes Knowde, a search interface with purely visual result representation. It employs a powerful information retrieval system and works in a common web browser in real-time. This working prototype, with three different variations of network graphs will assist us in exploring current issues in visualization research, such as the challenge of system evaluation. The final authenticated version is available online at https://doi.org/10.1007/978-3-319-92270-6_26

Evaluating a Visual Search Interface

Evaluation of information visualization and especially visual information systems is challenging. Metrics and methods need to be chosen with the intend of gaining specific and relevant evaluation data to prove the value of such systems. We suggest an evaluation based on the Information Service Evaluation Model (ISE) for information systems with visual result representation. We present the results of a case study on the testing and implementation of a visual search engine in business

Knowde - A Visual Search Interface

<p>Poster explaining the Knowde system. Accompanying the corresponding <a href="https://doi.org/10.5281/zenodo.1212228">publication</a> at the HCII 2018.</p