Camera-equipped Smartphone Research Articles

Validation of Argo (Automatic record generator for Onco-Hematology), a New App Supporting the Automatic Conversion of Paper-Based Pathology Reports in Standardized Ecrfs

Background and aims. The scarce accessibility to integrated systems limits the advantage of using real-world medical data for translational research purposes. ARGO (Automatic Report Generation for Onco-hematology) converts paper-based pathology reports in electronic Case Report Forms (eCRFs) exploiting Optical Character Recognition and Natural Language Processing technologies [Zaccaria et al., Sci. Rep., 2021]. Here, we present for the first time the App version of ARGO, designed to support physicians and data entries in rapidly generating eCRFs in a standardized and filtrable fashion. For scalability purposes, we tested ARGO App by processing n. 501 pathology reports from eight Italian Centers, including Hodgkin (HL), Diffuse Large B-Cell (DLBCL), Follicular (FCL), Mantle Cell (MCL), and T-Cell (TCL) lymphoma diagnoses. Methods. Validation involved six expert hematologists who generated eCRFs by simply acquiring photographs of each paper-based report using commercially available camera-equipped smartphones (Apple® iPhones, IOS version 15). The set included n. 347 and n. 154 reports from IRCCS Istituto Tumori 'Giovanni Paolo II’ (internal series, IS) and seven Italian cooperative Centers (external series, ES), respectively. Overall, they comprised n. 139 HL, n. 154 DLBCL, n. 109 FL, n. 76 MCL, n. 6 TCL, n. 17 unclassified describing major immunohistochemistry markers (IMs) as MYC, BCL2, BCL6, CD10, CD20, Cyclin D1, CD79a, CD15, CD30, PAX5, CD5, CD3, and Ki-67 proliferation index. The automatic process of diagnosis assignment by the ARGO algorithm (developed in Python) was imposed to depend on the highest matching rate between the detected IMs and corresponding classification as from the National Institute of Health in accordance with the International Classification of Diseases, 10th (ICD-10) and oncology (ICD-O) versions. To overcome potential misdiagnosis risk, a Random Forest (RF) model was trained on the IMs set of the IS, tested on the ES, and combined with ARGO algorithm. The performance of the App was assessed for accuracy and F1-score, which is a more sensitive metric. Results. The ARGO App includes two use-cases at prospectically acquiring and retrospectively reading reports by users (physicians and/or data-managers). The first use-case allows users to acquire pathology reports via mobile phone's camera. The second use-case leads to search patients’ data filtering by "Report ID", "Name", "Surname” and "Type of diagnosis". For each new record, ARGO converts information about patients’ demography, diagnosis, tissue of origin of samples (lymph-node, extra-nodal, bone marrow, and peripheral blood), and IMs expressions. ARGO successfully converted 490 (97.8%) reports into structured eCRFs (overall, n. 18,816 data). In terms of accuracy (Fig. 1A), MYC, Cyclin D1, CD79a, CD15, EMA, BCL2 (by fluorescent in situ hybridization), IgD, IgM, EBV, Ki-67 detection achieved among 85.7% and 99.4% in both series. BCL2, BCL6, CD10, CD20, CD30, PAX5, CD23, CD5, and CD45/LCA achieved among 65.1% and 85.6% for the IS and among 71.0% and 90.9% for the ES. MUM1 and CD3 achieved 56.2% and 71.4%, and 72.0% and 79.9% for IS and ES, respectively. Concerning the F1-score (Fig. 1B), although no significant differences were observed between the two series, on average, biomarkers gave a score that was lower of 20.2% for IS and 35.3% for ES compared to accuracy. Interestingly, Ki-67 proliferation index, MYC, CD10, CD20, Cyclin D1, CD79a, CD15, CD23, and CD5 achieved among 73.5% and 85.9% for the IS and among 72.4% and 85.5% for the ES. The capturing of diagnosis achieved 87.3% and 82.5% of accuracy, and 87.3% and 83.0% of F1-score for IS and ES, respectively. Focusing on individual diagnoses in the ES, HL, MCL, DLBCL, FCL, and TCL reached 90.0%, 88.5%, 84.9%, 76.5%, 33.3%, respectively. Of these n. 154 reports, n. 52 (34%) were detected by the sole ARGO algorithm, n. 28 (18%) by RF, n. 67 (43%) by a combination of both, while n. 7 (5%) remained unclassified. Conclusions. We validated ARGO App that robustly converts paper-based pathology reports of major lymphoma subtypes into structured eCRFs. ARGO is feasible and easily transferable into the daily practice to generate standardized patients’ clinical records for clinical and translational research purposes. Ongoing efforts are aiming at enlarging the TCL cohort of pathology reports and developing a multilanguage version for other languages than Italian. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Eyes on the ground and eyes in the sky: Security narratives, participatory visual methods and knowledge production in ‘danger zones’

This article reflects on the use of narrative interviews alongside participatory and remote-access visual methods to produce knowledge on and in conflict-affected settings. It details our iterative and reactive experiences of navigating transnational academic, policy and humanitarian networks to attempt to undertake ethical research on the security experiences of displaced people in Somali cities and facilitate their engagement with policymakers. We explore tensions in the combined use of increasingly accessible digital tools (camera-equipped smartphones and open-access satellite imagery) in facilitating a participatory, narrative-based approach to security research while also mitigating access limitations to research sites. We argue that a holistic and reflexive approach to everyday security within a technologically mediated data-collection process – for both researchers and research participants – not only is important for negotiations around ethical fieldwork, but also can be generative of findings about the research site itself. Methods are not brought into a context and deployed by researchers in ways that are fully under their control. In the case explored here, how the researchers and research participants engaged in dialogue about various methods, reflected their connections within networks of knowledge production dominated by humanitarian donors/partners, while also highlighting important aspects of displaced people’s everyday experiences of (in)security and marginalization in Somali cities.

Development of Attendance and Temperature Monitoring System using IoT with Wireless Power Transfer Application

Enclosed areas pose a greater risk of transmitting infectious and bacterial diseases. The proposed system helps prevent disease by tracking students’ daily body temperature before entering the school premises. Each student will be provided with a unique QR code containing the student information, such as their name and class. The QR code needs to be scanned first by the camera-equipped smartphone before reading the body temperature. The thermometer will record the student’s body temperature and send the information to the smartphone via Bluetooth. The student’s profile will be updated with the recorded daily temperature. An Android application will be developed to scan the QR code and display the students’ profiles and information. In order to design a battery-less system, the system will be integrated with a wireless power transfer circuit. Based on the simulation results, the wireless power transfer circuit can be used as a wireless charger for the smartphone used in the system or for charging the thermometer’ of the thermometer.

Smartphone picture organization: A hierarchical approach

We live in a society where the large majority of the population has a camera-equipped smartphone. In addition, hard drives and cloud storage are getting cheaper and cheaper, leading to a tremendous growth in stored personal photos. Unlike photo collections captured by a digital camera, which typically are pre-processed by the user who organizes them into event-related folders, smartphone pictures are automatically stored in the cloud. As a consequence, photo collections captured by a smartphone are highly unstructured and because smartphones are ubiquitous, they present a larger variability compared to pictures captured by a digital camera. To solve the need of organizing large smartphone photo collections automatically, we propose here a new methodology for hierarchical photo organization into topics and topic-related categories. Our approach successfully estimates latent topics in the pictures by applying probabilistic Latent Semantic Analysis, and automatically assigns a name to each topic by relying on a lexical database. Topic-related categories are then estimated by using a set of topic-specific Convolutional Neuronal Networks. To validate our approach, we ensemble and make public a large dataset of more than 8,000 smartphone pictures from 40 persons. Experimental results demonstrate major user satisfaction with respect to state of the art solutions in terms of organization.

Going on a Field Trip: Critical Geographical Walking Tours and Tactical Media as Urban Praxis in Sydney, Australia

Going on a Field Trip: Critical Geographical Walking Tours and Tactical Media as Urban Praxis in Sydney, Australia

Static Hand Gesture Recognition using an Android Device

The need to enhance communication between humans and computers has been instrumental in determining new communication models, and accordingly new ways of interacting with machines. A vision based Hand Gesture Recognition system can be useful to recognize hand gesture in air, with devices like camera equipped smart phones and cameras connected to computers. The fast improvement of smartphones during the last decade has been predominantly determined by interaction and visualization innovations. Despite the fact that touchscreens have significantly enhanced interaction technology, future smartphone clients will request more natural inputs, for example, free-hand association in 3D space. To extract the features of air gesture we used statistical technique which is Principal Component Analysis (PCA). The recognition approach used in this paper is based on Support Vector Machine (SVM). Proposed Hand Gesture System is location and orientation invariant. All the processes to recognize the hand gesture are done on the device. This approach can be easily adapted to a real time system.

Improving classroom visual accessibility with cooperative smartphone recordings

An earlier version of this paper was presented at the 2011 IEEE International Symposium on Technology and Society (ISTAS) at Saint Xavier University in Chicago, Illinois (and printed in the 2011 ISTAS proceedings). We propose a cooperative approach by students in recording lecture activities such that the classroom becomes more visually accessible for everyone, especially for deaf, hard of hearing and low-vision students. Students utilize their personal camera-equipped smart phones to capture and share their views of a visually inaccessible classroom to students' devices. We show this approach virtually retrofits a classroom to make it a more visually accessible learning environment. This approach can be used in meetings to get and share optimal views of the meeting for all participants.

Point and Shoot: Extending Your Reach with QR Codes

In the past few years, two-dimensional barcodes, including QR codes, have become commonplace. Businesses have embraced them as an easy way to provide information, including links to websites, videos, and contact information, to customers. Users can easily capture QR codes with a camera-equipped smartphone and a low-cost or free code-reader app. There are many easy and free resources for creating QR codes. Librarians are experimenting with creative ways to use QR codes to reach out to patrons.

Mobile Fair Diary: hybrid interface for taking, browsing and sharing context-aware notes

This paper describes the Mobile Fair Diary (MFD), which is designed to allow a housing fair customer to make a personalized digital recording of his/her visit to a hectic fairground for later use. The MFD is a hybrid interface service comprising of an application for a camera equipped smart phone and a website accessed by a PC. The smart phone application is used for taking context-aware notes such as visual codes, photos, dictations and text. The notes are uploaded onto a website, where they can be viewed with a PC in a contextually ordered view for browsing, organizing and sharing. The MFD was empirically evaluated in a real-life environment of use with genuine end users by a large-scale field trial at a national housing fair. The results testify to the very successful design of the MFD with high usefulness.