Role of deep learning in predicting aging-related diseases:A scoping review

Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an individual, over time. Aging-related diseases are highly prevalent and could impact an individual’s physical health. Recently, artificial intelligence (AI) methods have been used to predict aging-related diseases and issues, aiding clinical providers in decision-making based on patient’s medical records. Deep learning (DL), as one of the most recent generations of AI technologies, has embraced rapid progress in the early prediction and classification of aging-related issues. In this paper, a scoping review of publications using DL approaches to predict common aging-related diseases (such as age-related macular degeneration, cardiovascular and respiratory diseases, arthritis, Alzheimer’s and lifestyle patterns related to disease progression), was performed. Google Scholar, IEEE and PubMed are used to search DL papers on common aging-related issues published between January 2017 and August 2021. These papers were reviewed, evaluated, and the findings were summarized. Overall, 34 studies met the inclusion criteria. These studies indicate that DL could help clinicians in diagnosing disease at its early stages by mapping diagnostic predictions into observable clinical presentations; and achieving high predictive performance (e.g., more than 90% accurate predictions of diseases in aging)

Remote Screening And Self-Monitoring For Vision Loss Diseases Based On Smartphone Applications

Remote Healthcare Monitoring System (RHMS) represents remote observing of patient’s well-being and providing therapeutic services. Sensors play an essential part in RHMs. They measure the physical parameters and give continuous information to health organizations, doctors. The presence of Smartphones and other portable devices have allowed us to utilize remote healthcare monitoring system for an assortment of structures. Also, Wireless Sensor Network (WSN) advances considered as one of the critical research factor healthcare application for enhancing the standard of living. In this dissertation, I have presented three tiers operating in the remote healthcare monitoring system; the Body Area Network (BAN), the PAN Coordinator and the Back- Medical End System (BMEsys). The three tiers focused on several patients PAN coordinators include the Wireless Sensor Network. The Wireless Sensor Network can be used at the fixed tale-monitor location and periodic measurements. The Personal Digital Assistant (PDA) can be used in patients own home or community setting with continuous measurements and smartphones can be utilized anywhere with full range parameters, and I have provided a meaningful utilization comparison between Wireless Sensor Network, PDA and smartphone in Remote Healthcare Monitoring System (HRMs) architecture design. Evaluate the approaches of the healthcare monitoring system architecture and investigate the use of advanced technologies enabling the patient vital signs and diagnostic medical team in real-time. This dissertation demonstrates that how a Smartphone can be used for medical treatment in the field of Ophthalmology and discussed how a Smartphone and its technology could be used to diagnose loss of eye vision. Most recent smartphones have been equipped with a featured camera with high megapixels and advanced sensors which can be used to record fundus photographs through a slit lamp or record videos from an operating microscope and display images from optical coherence tomography systems and other high-tech devices. The ophthalmologists can share these images and analyze with their colleagues utilizing media sharing applications and make the optimal diagnostic and therapeutic results to diagnose the low vision of patients. At present, three widely used pocket-sized adapters can improve the magnification and lighting of the camera, which enables the smartphones to capture high-quality images of the eye. These are Portable Eye Examination Kit (PEEK), EyeGo, and D-Eye. Peek Adapter consists of a smartphone application and retina adapter which can be clipped onto the device and synchronized with the peek application for sharing and analyzing the images. This adapter can be used by anyone and anywhere in the world to examine eyes. EyeGo is an adapter intended to allow ophthalmologists and healthcare specialists to capture high-quality images of the eye using an ophthalmic lens. D-Eye Adapter is one of the extensively used adapters which yield excellent results. It consists of a portable eye and retinal system that fits onto a smartphone creating a retinal camera for evaluation and screening of the eye. It uses LED lights as a light source and requires no extra power, making it an ideal solution for portable diagnostics. The medical field has widely accepted these adaptors with the smartphones for diagnosing low vision and eye-related infections. In this dissertation, I also provide a meaningful utilization comparison between the smartphone adapters: D-Eye, EyeGo and Portable Eye Examination Kit (PEEK). In this dissertation, I have developed a new App (Remote Healthcare-Monitoring Mobile App) to help patients who have low vision and who are suffering from the diseases which may cause a vision loss. This app is capable of a process, evaluate, interact and store health data which is continuously measured by (Personal Health Monitors). This App can exchange the information directly to the Smartphone users (patients) and the doctor who allows more security and privacy. The idea of the App consists of the following: A Smartphone Application, a Data Collection Center, and Professionals in Ophthalmology. The patient should be registered in the system, for example, (Retina Michigan Center or Glaucoma Michigan Center). After registration, the patient is instructed on how to take photos of his/her eyes correctly, and then use the Smartphone application. The patient takes photos of his/her eyes and sends them to the data collection center, the specialists get access to these data and help in the treatment according to the analysis. Finally, I completed the development of the Mobile app (including the Skype and Viber links), which can help in exchanging the information between the patient and the doctor

Enablers and Barriers to Deployment of Smartphone-Based Home Vision Monitoring in Clinical Practice Settings

Importance: Telemedicine is accelerating the remote detection and monitoring of medical conditions, such as vision-threatening diseases. Meaningful deployment of smartphone apps for home vision monitoring should consider the barriers to patient uptake and engagement and address issues around digital exclusion in vulnerable patient populations. Objective: To quantify the associations between patient characteristics and clinical measures with vision monitoring app uptake and engagement. Design, Setting, and Participants: In this cohort and survey study, consecutive adult patients attending Moorfields Eye Hospital receiving intravitreal injections for retinal disease between May 2020 and February 2021 were included. Exposures: Patients were offered the Home Vision Monitor (HVM) smartphone app to self-test their vision. A patient survey was conducted to capture their experience. App data, demographic characteristics, survey results, and clinical data from the electronic health record were analyzed via regression and machine learning. Main Outcomes and Measures: Associations of patient uptake, compliance, and use rate measured in odds ratios (ORs). Results: Of 417 included patients, 236 (56.6%) were female, and the mean (SD) age was 72.8 (12.8) years. A total of 258 patients (61.9%) were active users. Uptake was negatively associated with age (OR, 0.98; 95% CI, 0.97-0.998; P = .02) and positively associated with both visual acuity in the better-seeing eye (OR, 1.02; 95% CI, 1.00-1.03; P = .01) and baseline number of intravitreal injections (OR, 1.01; 95% CI, 1.00-1.02; P = .02). Of 258 active patients, 166 (64.3%) fulfilled the definition of compliance. Compliance was associated with patients diagnosed with neovascular age-related macular degeneration (OR, 1.94; 95% CI, 1.07-3.53; P = .002), White British ethnicity (OR, 1.69; 95% CI, 0.96-3.01; P = .02), and visual acuity in the better-seeing eye at baseline (OR, 1.02; 95% CI, 1.01-1.04; P = .04). Use rate was higher with increasing levels of comfort with use of modern technologies (β = 0.031; 95% CI, 0.007-0.055; P = .02). A total of 119 patients (98.4%) found the app either easy or very easy to use, while 96 (82.1%) experienced increased reassurance from using the app. Conclusions and Relevance: This evaluation of home vision monitoring for patients with common vision-threatening disease within a clinical practice setting revealed demographic, clinical, and patient-related factors associated with patient uptake and engagement. These insights inform targeted interventions to address risks of digital exclusion with smartphone-based medical devices

Patient acceptability of home monitoring for neovascular age-related macular degeneration reactivation:a qualitative study

Neovascular age-related macular degeneration (nAMD) is a chronic, progressive condition and the commonest cause of visual disability in older adults. This study formed part of a diagnostic test accuracy study to quantify the ability of three index home monitoring (HM) tests (one paper-based and two digital tests) to identify reactivation in nAMD. The aim of this qualitative research was to investigate patients’ or participants’ views about acceptability and explore adherence to weekly HM. Semi-structured interviews were held with 78/297 participants (26%), with close family members (n = 11) and with healthcare professionals involved in training participants in HM procedures (n = 9) (n = 98 in total). A directed thematic analytical approach was applied to the data using a deductive and inductive coding framework informed by theories of technology acceptance. Five themes emerged related to: 1. The role of HM; 2. Suitability of procedures and instruments; 3. Experience of HM; 4. Feasibility of HM in usual practice; and 5. Impediments to patient acceptability of HM. Various factors influenced acceptability including a patient’s understanding about the purpose of monitoring. While initial training and ongoing support were regarded as essential for overcoming unfamiliarity with use of digital technology, patients viewed HM as relatively straightforward and non-burdensome. There is a need for further research about how use of performance feedback, level of support and nature of tailoring might facilitate further the implementation of routinely conducted HM. Home monitoring was acceptable to patients and they recognised its potential to reduce clinic visits during non-active treatment phases. Findings have implications for implementation of digital HM in the care of older people with nAMD and other long-term conditions

Ophthalmic sensing technologies for ocular disease diagnostics

Point-of-care diagnosis and personalized treatments are critical in ocular physiology and disease. Continuous sampling of tear fluid for ocular diagnosis is a need for further exploration. Several techniques have been developed for possible ophthalmological applications, from traditional spectroscopies to wearable sensors. Contact lenses are commonly used devices for vision correction, as well as for other therapeutic and cosmetic purposes. They are increasingly being developed into ocular sensors, being used to sense and monitor biochemical analytes in tear fluid, ocular surface temperature, intraocular pressure, and pH value. These sensors have had success in detecting ocular conditions, optimizing pharmaceutical treatments, and tracking treatment efficacy in point-of-care settings. However, there is a paucity of new and effective instrumentation reported in ophthalmology. Hence, this review will summarize the applied ophthalmic technologies for ocular diagnostics and tear monitoring, including both conventional and biosensing technologies. Besides applications of smart readout devices for continuous monitoring, targeted biomarkers are also discussed for the convenience of diagnosis of various ocular diseases. A further discussion is also provided for future aspects and market requirements related to the commercialization of novel types of contact lens sensors

Participatory design:how to engage older adults in participatory design activities

Ongoing advances in mobile technologies have the potential to improve independence and quality of life of older adults by supporting the delivery of personalised and ubiquitous healthcare solutions. The authors are actively engaged in participatory, user-focused research to create a mobile assistive healthcare-related intervention for persons with age-related macular degeneration (AMD): the authors report here on our participatory research in which participatory design (PD) has been positively adopted and adapted for the design of our mobile assistive technology. The authors discuss their work as a case study in order to outline the practicalities and highlight the benefits of participatory research for the design of technology for (and importantly with) older adults. The authors argue it is largely impossible to achieve informed and effective design and development of healthcare-related technologies without employing participatory approaches, and outline recommendations for engaging in participatory design with older adults (with impairments) based on practical experience

Automating the eye examination using optical coherence tomography

Optical coherence tomography (OCT) devices are becoming ubiquitous in eye clinics worldwide to aid the diagnosis and monitoring of eye disease. Much of this uptake relates to the ability to non-invasively capture micron-resolution images, enabling objective and quantitative data to be obtained from ocular structures. Although safe and reasonably quick to perform, the costs involved with operating OCT devices are not trivial, and the requirement for OCT and other imaging in addition to other clinical measures is placing increasing demand on ophthalmology clinics, contributing to fragmented patient pathways and often extended waiting times. In this thesis, a novel “binocular optical coherence tomography” system that seeks to overcome some of the limitations of current commercial OCT systems, is clinically evaluated. This device incorporates many aspects of the eye examination into a single patient-operated instrument, and aims to improve the efficiency and quality of eye care while reducing the overall labour and equipment costs. A progressive framework of testing is followed that includes human factors and usability testing, followed by early stage diagnostic studies to assess the agreement, repeatability, and reproducibility of individual diagnostic features. Health economics analysis of the retinal therapy clinic is used to model cost effectiveness of current practice and with binocular OCT implementation. The binocular OCT and development of other low-cost OCT systems may improve accessibility, however there remains a relative shortage of experts to interpret the images. Artificial intelligence (AI) is likely to play a role in rapid and automated image classification. This thesis explores the application of AI within retinal therapy clinics to predict the onset of exudative age-related macular degeneration in fellow eyes of patients undergoing treatment in their first eye. Together with automated and simultaneous imaging of both eyes with binocular OCT and the potential for low-cost patient-facing systems, AI is likely to have a role in personalising management plans, especially in a future where preventive treatments are available