Urology apps: overview of current types and use

Mantica, Guglielmo; Malinaric, Rafaela; Dotta, Federico; Paraboschi, Irene; Guano, Giovanni; Rebuffo, Silvia; Garriboli, Massimo; Suardi, Nazareno; Merwe, André van der; Terrone, Carlo

doi:10.5173/ceju.2020.0090

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…Since deep learning algorithms rely on high-volume, the next step to increase robustness of this system will be to collect and integrate real-life intraoperative PC images from multiple different medical centers. Since smartphone technology is already being employed by patients and care providers across a range of medical applications, this approach may also present opportunities to further develop patient–provider relationships (Mantica et al, 2020 ). Employing consistent methods that more accurately define hypospadias phenotype, PC extent, and inform surgical technique should lead to improved outcomes for affected patients.…”

Section: Discussionmentioning

confidence: 99%

Automated quantification of penile curvature using artificial intelligence

Abbas

AbdelMoniem

Chowdhury

2022

Front. Artif. Intell.

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ObjectiveTo develop and validate an artificial intelligence (AI)-based algorithm for capturing automated measurements of Penile curvature (PC) based on 2-dimensional images.Materials and methodsNine 3D-printed penile models with differing curvature angles (ranging from 18 to 88°) were used to compile a 900-image dataset featuring multiple camera positions, inclination angles, and background/lighting conditions. The proposed framework of PC angle estimation consisted of three stages: automatic penile area localization, shaft segmentation, and curvature angle estimation. The penile model images were captured using a smartphone camera and used to train and test a Yolov5 model that automatically cropped the penile area from each image. Next, an Unet-based segmentation model was trained, validated, and tested to segment the penile shaft, before a custom Hough-Transform-based angle estimation technique was used to evaluate degree of PC.ResultsThe proposed framework displayed robust performance in cropping the penile area [mean average precision (mAP) 99.4%] and segmenting the shaft [Dice Similarity Coefficient (DSC) 98.4%]. Curvature angle estimation technique generally demonstrated excellent performance, with a mean absolute error (MAE) of just 8.5 when compared with ground truth curvature angles.ConclusionsConsidering current intra- and inter-surgeon variability of PC assessments, the framework reported here could significantly improve precision of PC measurements by surgeons and hypospadiology researchers.

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Section: Discussionmentioning

confidence: 99%

Automated quantification of penile curvature using artificial intelligence

Abbas

AbdelMoniem

Chowdhury

2022

Front. Artif. Intell.

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“…Studies support the need for expert involvement in mobile app development, dissemination, and regulation [15,16,18,19]. In our study, patients were unanimously willing to share this health data with their clinicians with the goal of optimizing their urologic care.…”

Section: Discussionmentioning

confidence: 70%

“…Most American men and adults over the age of 65 years own a smartphone [14]. Mobile apps are widely used by the general public, and the number of urology-related mobile apps has multiplied in recent decades [15]. These apps support patients with a wide range of urologic conditions, but their usage is unstandardized and unregulated [16]; in addition, mobile app usage remains inconsistently integrated with routine clinical care [17].…”

Section: Discussionmentioning

confidence: 99%

Perceptions of Older Men Using a Mobile Health App to Monitor Lower Urinary Tract Symptoms and Tamsulosin Side Effects: Mixed Methods Study

Wang¹,

Breyer²,

Lee³

et al. 2021

JMIR Hum Factors

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Background Mobile health (mHealth) apps may provide an efficient way for patients with lower urinary tract symptoms (LUTS) to log and communicate symptoms and medication side effects with their clinicians. Objective The aim of this study was to explore the perceptions of older men with LUTS after using an mHealth app to track their symptoms and tamsulosin side effects. Methods Structured phone interviews were conducted after a 2-week study piloting the daily use of a mobile app to track the severity of patient-selected LUTS and tamsulosin side effects. Quantitative and qualitative data were considered. Results All 19 (100%) pilot study participants completed the poststudy interviews. Most of the men (n=13, 68%) reported that the daily questionnaires were the right length, with 32% (n=6) reporting that the questionnaires were too short. Men with more severe symptoms were less likely to report changes in perception of health or changes in self-management; 47% (n=9) of the men reported improved awareness of symptoms and 5% (n=1) adjusted fluid intake based on the questionnaire. All of the men were willing to share app data with their clinicians. Thematic analysis of qualitative data yielded eight themes: (1) orientation (setting up app, format, symptom selection, and side-effect selection), (2) triggers (routine or habit and symptom timing), (3) daily questionnaire (reporting symptoms, reporting side effects, and tailoring), (4) technology literacy, (5) perceptions (awareness, causation or relevance, data quality, convenience, usefulness, and other apps), (6) self-management, (7) clinician engagement (communication and efficiency), and (8) improvement (reference materials, flexibility, language, management recommendations, and optimize clinician engagement). Conclusions We assessed the perceptions of men using an mHealth app to monitor and improve management of LUTS and medication side effects. LUTS management may be further optimized by tailoring the mobile app experience to meet patients’ individual needs, such as tracking a greater number of symptoms and integrating the app with clinicians’ visits. mHealth apps are likely a scalable modality to monitor symptoms and improve care of older men with LUTS. Further study is required to determine the best ways to tailor the mobile app and to communicate data to clinicians or incorporate data into the electronical medical record meaningfully.

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“…Die Erstellung eines umfassenden Überblicks im Fach Urologie bleibt aufgrund der beständig neu aufkommenden Apps anspruchsvoll. Zudem stellt auch deren Bewertung in Hinblick auf Qualität und Datenschutz angesichts fehlender, standardisierter Bewertungsmechanismen eine Herausforderung dar [5]. Mit dem digitalen Versorgungsgesetz (DVG; [6]) ist es Ärzt:innen seit Dezember 2019 möglich, geprüfte Apps unter Kostenübernahme sowie unter Vergütung der damit verbundenen ärztlichen Leistungen durch die Krankenkassen per Rezept (Muster 16) zu verordnen.…”

Section: In Diesem Beitragunclassified

Viel Potenzial, wenig Substanz

Mattigk

Bellut

Albrecht

et al. 2021

Urologe

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Great potential, little substance. Overview of quality and quantity of urological apps in the German app storeBackground: The range of medical apps is broad and diverse. The previous evaluations are inconsistent and limited to the respective areas of application. Objectives: The main objective of this work is to comprehensively present, organize, and evaluate the current range of urological apps with the help of a semi-automatic retrospective app store analysis (SARASA). Methods: Application of an adaptable method based on filter processes according to predefined criteria by means of SARASA to characterize urological apps from various subject areas in the Apple App Store with subsequent manual filtering and evaluation. Results: From the original list of 34,830 apps in the "Medicine" category of the Apple App Store on 27 September 2021, 3556 apps remained after apps without a Germanlanguage store description were removed. 43 subject-specific apps remained for further analysis and description. The number of reviews, rating, topicality, urological issues, technical support and richness of content were taken into account. The two most relevant apps for each topic are presented in detail. Conclusion: SARASA offers an easy-to-use method for applying filter processes to identify apps in app stores that meet predefined, formal criteria. The highest number of apps can be classified in categories of patient information and further education and training. An app officially listed by the German Federal Institute for Drugs and Medical Products (BfArM) in the sense of a digital health application (DiGA), the costs of which are reimbursed by the health insurance companies, is available for urology in only one single case. The authors see great potential for future developments in this regard.

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Urology apps: overview of current types and use

Cited by 7 publications

References 9 publications

Automated quantification of penile curvature using artificial intelligence

Automated quantification of penile curvature using artificial intelligence

Perceptions of Older Men Using a Mobile Health App to Monitor Lower Urinary Tract Symptoms and Tamsulosin Side Effects: Mixed Methods Study

Viel Potenzial, wenig Substanz

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