Does Testing More Frequently Shorten the Time to Detect Disease Progression?

Machine Learning Techniques for Developing Remotely Monitored Central Nervous System Biomarkers Using Wearable Sensors: A Narrative Literature Review

BACKGROUND

Central nervous system (CNS) disorders benefit from ongoing monitoring to assess disease progression and treatment efficacy. Mobile health (mHealth) technologies offer a means for the remote and continuous symptom monitoring of patients. Machine Learning (ML) techniques can process and engineer mHealth data into a precise and multidimensional biomarker of disease activity.

OBJECTIVE

This narrative literature review aims to provide an overview of the current landscape of biomarker development using mHealth technologies and ML. Additionally, it proposes recommendations to ensure the accuracy, reliability, and interpretability of these biomarkers.

METHODS

This review extracted relevant publications from databases such as PubMed, IEEE, and CTTI. The ML methods employed across the selected publications were then extracted, aggregated, and reviewed.

RESULTS

This review synthesized and presented the diverse approaches of 66 publications that address creating mHealth-based biomarkers using ML. The reviewed publications provide a foundation for effective biomarker development and offer recommendations for creating representative, reproducible, and interpretable biomarkers for future clinical trials.

CONCLUSION

mHealth-based and ML-derived biomarkers have great potential for the remote monitoring of CNS disorders. However, further research and standardization of study designs are needed to advance this field. With continued innovation, mHealth-based biomarkers hold promise for improving the monitoring of CNS disorders.

Artificial intelligence manages congenital cataract with individualized prediction and telehealth computing

A challenge of chronic diseases that remains to be solved is how to liberate patients and medical resources from the burdens of long-term monitoring and periodic visits. Precise management based on artificial intelligence (AI) holds great promise; however, a clinical application that fully integrates prediction and telehealth computing has not been achieved, and further efforts are required to validate its real-world benefits. Taking congenital cataract as a representative, we used Bayesian and deep-learning algorithms to create CC-Guardian, an AI agent that incorporates individualized prediction and scheduling, and intelligent telehealth follow-up computing. Our agent exhibits high sensitivity and specificity in both internal and multi-resource validation. We integrate our agent with a web-based smartphone app and prototype a prediction-telehealth cloud platform to support our intelligent follow-up system. We then conduct a retrospective self-controlled test validating that our system not only accurately detects and addresses complications at earlier stages, but also reduces the socioeconomic burdens compared to conventional methods. This study represents a pioneering step in applying AI to achieve real medical benefits and demonstrates a novel strategy for the effective management of chronic diseases.

Clinical Evaluation of Swedish Interactive Thresholding Algorithm-Faster Compared With Swedish Interactive Thresholding Algorithm-Standard in Normal Subjects, Glaucoma Suspects, and Patients With Glaucoma

PURPOSE

To compare the visual fields results obtained using the Swedish interactive thresholding algorithm-Standard (SS) and the Swedish interactive thresholding algorithm-Faster (SFR) in normal subjects, glaucoma suspects, and patients with glaucoma and to quantify potential time-saving benefits of the SFR algorithm.

DESIGN

Prospective, cross-sectional study.

METHODS

One randomly selected eye from 364 patients (77 normal subjects, 178 glaucoma suspects, and 109 patients with glaucoma) seen in a single institution underwent testing using both SS and SFR on the Humphrey Field Analyzer. Cumulative test time using each algorithm was compared after accounting for different rates of test reliability. Pointwise and cluster analysis was performed to determine whether there were systematic differences between algorithms.

RESULTS

Using SFR had a greater rate of unreliable results (29.3%) compared with SS (7.7%, P < .0001). This was mainly because of high false positive rates and seeding point errors. However, modeled test times showed that using SFR could obtain a greater number of reliable results within a shorter period of time. SFR resulted in higher sensitivity values (on average 0.5 dB for patients with glaucoma) that was greater under conditions of field loss (<19 dB). Cluster analysis showed no systematic patterns of sensitivity differences between algorithms.

CONCLUSIONS

After accounting for different rates of test reliability, SFR can result in significant time savings compared with SS. Clinicians should be cognizant of false positive rates and seeding point errors as common sources of error for SFR. Results between algorithms are not directly interchangeable, especially if there is a visual field deficit <19 dB.

Differences in the Relation Between Perimetric Sensitivity and Variability Between Locations Across the Visual Field

Purpose

Perimetric sensitivities become more variable with glaucomatous functional loss. This study examines the extent to which this relation varies between locations, and whether this can be predicted by eccentricity-related differences in spatial summation.

Methods

Longitudinal series of visual fields from standard automated perimetry were obtained from participants with suspected or extant glaucoma. For each location in the 24-2 visual field, heterogeneous fixed-effects models were fit to the data, assuming that variability increased exponentially as sensitivity decreased. The predicted variability at each location was calculated when sensitivity was either 30 dB or 25 dB.

Results

Variability significantly increased with damage at all 52 locations. When sensitivity was 30 dB, variability increased with eccentricity, with P = 0.0003. The average SD was 1.54 dB at the four most central locations, versus 1.74 dB at the most peripheral locations. When sensitivity was 25 dB, variability did not vary predictably with eccentricity, with P = 0.340. The average SD was 2.36 dB at the four central locations, versus 2.24 dB at the most peripheral locations.

Conclusions

The relation between sensitivity and variability differed by eccentricity. Among healthy locations, variability was lower centrally, where the stimulus size is larger than Ricco's area, than peripherally. Among damaged locations, variability did not systematically vary with eccentricity. This could be because Ricco's area expands in glaucoma, such that stimuli were now smaller than this area at all locations.

Safety and Feasibility of a Novel Sparse Optical Coherence Tomography Device for Patient-Delivered Retina Home Monitoring

Purpose

To study a novel and fast optical coherence tomography (OCT) device for home-based monitoring in age-related macular degeneration (AMD) in a small sample yielding sparse OCT (spOCT) data and to compare the device to a commercially available reference device.

Methods

In this prospective study, both eyes of 31 participants with AMD were included. The subjects underwent scanning with an OCT prototype and a spectral-domain OCT to compare the accuracy of the central retinal thickness (CRT) measurements.

Results

Sixty-two eyes in 31 participants (21 females and 10 males) were included. The mean age was 79.6 years (age range, 69–92 years). The mean difference in the CRT measurements between the devices was 4.52 μm (SD ± 20.0 μm; range, −65.6 to 41.5 μm). The inter- and intrarater reliability coefficients of the OCT prototype were both >0.95. The laser power delivered was <0.54 mW for spOCT and <1.4 mW for SDOCT. No adverse events were reported, and the visual acuity before and after the measurements was stable.

Conclusion

This study demonstrated the safety and feasibility of this home-based OCT monitoring under real-life conditions, and it provided evidence for the potential clinical benefit of the device.

Translational Relevance

The newly developed spOCT is a valid and readily available retina scanner. It could be applied as a portable self-measuring OCT system. Its use may facilitate the sustainable monitoring of chronic retinal diseases by providing easily accessible and continuous retinal monitoring.