Computer-assisted medical history taking prior to patient consultation in the outpatient care setting: a prospective pilot project.

Background: Feeding patients' self-reported medical history into the diagnostic care process may accelerate workflows in clinical routine.

Methods: We prospectively piloted a novel medical history documentation system in a German cardiological outpatient practice and evaluated its feasibility and perceived usefulness. Based on a generic software that allows to record structured information, a customized solution for the cooperating practice was developed and implemented.

Integrated Simulation and Calibration Framework for Heating System Optimization.

In a time where sustainability and CO2 efficiency are of ever-increasing importance, heating systems deserve special considerations. Despite well-functioning hardware, inefficiencies may arise when controller parameters are not well chosen. While monitoring systems could help to identify such issues, they lack improvement suggestions.

Direct comparison of multiple computer-aided polyp detection systems.

Background And Study Aims:  Artificial intelligence (AI)-based systems for computer-aided detection (CADe) of polyps receive regular updates and occasionally offer customizable detection thresholds, both of which impact their performance, but little is known about these effects. This study aimed to compare the performance of different CADe systems on the same benchmark dataset.

Methods:  101 colonoscopy videos were used as benchmark.

Using a Clinical Data Warehouse to Calculate and Present Key Metrics for the Radiology Department: Implementation and Performance Evaluation.

Background: Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals.

Objective: This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI).

Methods: Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file.

Automated classification of polyps using deep learning architectures and few-shot learning.

Background: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous.

A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks.

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist searches for polyps.

Querying a Clinical Data Warehouse for Combinations of Clinical and Imaging Data.

This study aims to show the feasibility and benefit of single queries in a research data warehouse combining data from a hospital's clinical and imaging systems. We used a comprehensive integration of a production picture archiving and communication system (PACS) with a clinical data warehouse (CDW) for research to create a system that allows data from both domains to be queried jointly with a single query. To achieve this, we mapped the DICOM information model to the extended entity-attribute-value (EAV) data model of a CDW, which allows data linkage and query constraints on multiple levels: the patient, the encounter, a document, and a group level.

HIOP-Reader: Automated Data Extraction for the Analysis of Manually Recorded Nycthemeral IOPs and Glaucoma Progression.

Purpose: Nycthemeral (24-hour) intraocular pressure (IOP) monitoring in glaucoma has been used in Europe for more than 100 years to detect peaks missed during regular office hours. Data supporting this practice are lacking, because it is difficult to correlate manually drawn IOP curves to objective glaucoma progression. To address this, we developed an automated IOP data extraction tool, HIOP-Reader.

A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems.

Background And Aims: Computer-aided polyp detection (CADe) may become a standard for polyp detection during colonoscopy. Several systems are already commercially available. We report on a video-based benchmark technique for the first preclinical assessment of such systems before comparative randomized trials are to be undertaken.

Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists.

Background: Machine learning, especially deep learning, is becoming more and more relevant in research and development in the medical domain. For all the supervised deep learning applications, data is the most critical factor in securing successful implementation and sustaining the progress of the machine learning model. Especially gastroenterological data, which often involves endoscopic videos, are cumbersome to annotate.

Pilot study of a new freely available computer-aided polyp detection system in clinical practice.

Purpose: Computer-aided polyp detection (CADe) systems for colonoscopy are already presented to increase adenoma detection rate (ADR) in randomized clinical trials. Those commercially available closed systems often do not allow for data collection and algorithm optimization, for example regarding the usage of different endoscopy processors. Here, we present the first clinical experiences of a, for research purposes publicly available, CADe system.

Inter-eye correlation analysis of 24-h IOPs and glaucoma progression.

Purpose: To determine whether 24-h IOP monitoring can be a predictor for glaucoma progression and to analyze the inter-eye relationship of IOP, perfusion, and progression parameters.

Methods: We extracted data from manually drawn IOP curves with HIOP-Reader, a software suite we developed. The relationship between measured IOPs and mean ocular perfusion pressures (MOPP) to retinal nerve fiber layer (RNFL) thickness was analyzed.

Automated provision of clinical routine data for a complex clinical follow-up study: A data warehouse solution.

A deep integration of routine care and research remains challenging in many respects. We aimed to show the feasibility of an automated transformation and transfer process feeding deeply structured data with a high level of granularity collected for a clinical prospective cohort study from our hospital information system to the study's electronic data capture system, while accounting for study-specific data and visits. We developed a system integrating all necessary software and organizational processes then used in the study.

New concept for colonoscopy including side optics and artificial intelligence.

Background And Aims: Adenoma detection rate is the crucial parameter for colorectal cancer screening. Increasing the field of view with additional side optics has been reported to detect flat adenomas hidden behind folds. Furthermore, artificial intelligence (AI) has also recently been introduced to detect more adenomas.

Calculating Key Figures for Radiology Departments Using a Clinical Data Warehouse - A Technical Case Report.

Optimizing the utilization of radiology departments is one of the primary objectives for many hospitals. To support this, a solution has been developed, which at first transforms the export of different Radiological Information Systems (RIS) into the data format of a clinical data warehouse (CDW). Additional features, like for example the time between the creation of a radiologic request and the finalization of the diagnosis for the created images, can then be defined using a simple interface and are calculated and saved in the CDW as well.

Semi-Automated Machine Learning Video Annotation for Gastroenterologists.

A semi-automatic tool for fast and accurate annotation of endoscopic videos utilizing trained object detection models is presented. A novel workflow is implemented and the preliminary results suggest that the annotation process is nearly twice as fast with our novel tool compared to the current state of the art.

Unlocking the PACS DICOM Domain for its Use in Clinical Research Data Warehouses.

Clinical Data Warehouses (DWHs) are used to provide researchers with simplified access to pseudonymized and homogenized clinical routine data from multiple primary systems. Experience with the integration of imaging and metadata from picture archiving and communication systems (PACS), however, is rare. Our goal was therefore to analyze the viability of integrating a production PACS with a research DWH to enable DWH queries combining clinical and medical imaging metadata and to enable the DWH to display and download images ad hoc.

Information Extraction from Echocardiography Reports for a Clinical Follow-up Study-Comparison of Extracted Variables Intended for General Use in a Data Warehouse with Those Intended Specifically for the Study.

Background:  The interest in information extraction from clinical reports for secondary data use is increasing. But experience with the productive use of information extraction processes over time is scarce. A clinical data warehouse has been in use at our university hospital for several years, which also provides an information extraction of echocardiography reports developed for general use.

Implementation of a HL7-CQL Engine Using the Graph Database Neo4J.

The Clinical Quality Language (CQL) is a useful tool for defining search requests for data stores containing FHIR data. Unfortunately, there are only few execution engines that are able to evaluate CQL queries. As FHIR data represents a graph structure, the authors pursue the approach of storing all data contained in a FHIR server in the graph database Neo4J and to translate CQL queries into Neo4J's query language Cypher.

Query Translation Between AQL and CQL.

Secondary use of electronic health records using data aggregation systems (DAS) with standardized access interfaces (e.g. openEHR, i2b2, FHIR) have become an attractive approach to support clinical research.

Exploration of Artificial Intelligence Use with ARIES in Multiple Myeloma Research.

Background: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text.

Efficacy of a web-based intervention for improving psychosocial well-being in patients with implantable cardioverter-defibrillators: the randomized controlled ICD-FORUM trial.

Aims: Anxiety, depression, and reduced quality of life (QoL) are common in patients with implantable cardioverter-defibrillators (ICDs). Treatment options are limited and insufficiently defined. We evaluated the efficacy of a web-based intervention (WBI) vs.

Evaluation of Patient's Attitude Towards Computer Supported History Taking.

We provide a highly integrated tool to conduct dynamic, multilingual anamnesis interviews with patients to enhance documentation and provide physicians with more time for patient interaction in an outpatient setting. A first analysis of patients' satisfaction with the user interface shows a high rate of acceptance and prompts further research.