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NPJ Digital Medicine Jun 2024The discovery of patterns associated with diagnosis, prognosis, and therapy response in digital pathology images often requires intractable labeling of large quantities...
The discovery of patterns associated with diagnosis, prognosis, and therapy response in digital pathology images often requires intractable labeling of large quantities of histological objects. Here we release an open-source labeling tool, PatchSorter, which integrates deep learning with an intuitive web interface. Using >100,000 objects, we demonstrate a >7x improvement in labels per second over unaided labeling, with minimal impact on labeling accuracy, thus enabling high-throughput labeling of large datasets.
PubMed: 38902336
DOI: 10.1038/s41746-024-01150-4 -
PloS One 2024Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for...
Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation process. In our model, CA3 provides a pre-trained sequence that is hetero-associated with the input sequence, rather than storing a sequence in CA3. That is, plasticity on a short timescale only occurs in the incoming and outgoing connections of CA3, not in its recurrent connections. We use a single learning rule named Hebbian descent to train all plastic synapses in the network. A forgetting mechanism in the learning rule allows the network to continuously store new patterns while forgetting those stored earlier. We find that a single cue pattern can reliably trigger the retrieval of sequences, even when cues are noisy or missing information. Furthermore, pattern separation in subregion DG is necessary when sequences contain correlated patterns. Besides artificially generated input sequences, the model works with sequences of handwritten digits and natural images. Notably, our model is capable of improving itself without external input, in a process that can be referred to as 'replay' or 'offline-learning', which helps in improving the associations and consolidating the learned patterns.
Topics: Neural Networks, Computer; Models, Neurological; Humans; Neuronal Plasticity; Learning; Hippocampus; Synapses
PubMed: 38900733
DOI: 10.1371/journal.pone.0304076 -
JMIR Formative Research Jun 2024Mobile health (mHealth) apps have proven useful for people with multiple sclerosis (MS). Thus, easy-to-use digital solutions are now strongly required to assess and...
BACKGROUND
Mobile health (mHealth) apps have proven useful for people with multiple sclerosis (MS). Thus, easy-to-use digital solutions are now strongly required to assess and monitor cognitive impairment, one of the most disturbing symptoms in MS that is experienced by almost 43% to 70% of people with MS. Therefore, we developed DIGICOG-MS (Digital assessment of Cognitive Impairment in Multiple Sclerosis), a smartphone- and tablet-based mHealth app to self-assess cognitive impairment in MS.
OBJECTIVE
This study aimed to test the validity and usability of the novel mHealth app with a sample of people with MS.
METHODS
DIGICOG-MS includes 4 digital tests assumed to evaluate the most affected cognitive domains in MS (visuospatial memory [VSM], verbal memory [VM], semantic fluency [SF], and information processing speed [IPS]) and inspired by traditional paper-based tests that assess the same cognitive functions (10/36 Spatial Recall Test, Rey Auditory Verbal Learning Test, Word List Generation, Symbol Digit Modalities Test). Participants were asked to complete both digital and traditional assessments in 2 separate sessions. Convergent validity was analyzed using the Pearson correlation coefficient to determine the strength of the associations between digital and traditional tests. To test the app's reliability, the agreement between 2 repeated measurements was assessed using intraclass correlation coefficients (ICCs). Usability of DIGICOG-MS was evaluated using the System Usability Scale (SUS) and mHealth App Usability Questionnaire (MAUQ) administered at the conclusion of the digital session.
RESULTS
The final sample consisted of 92 people with MS (60 women) followed as outpatients at the Italian Multiple Sclerosis Society (AISM) Rehabilitation Service of Genoa (Italy). They had a mean age of 51.38 (SD 11.36) years, education duration of 13.07 (SD 2.74) years, disease duration of 12.91 (SD 9.51) years, and a disability level (Expanded Disability Status Scale) of 3.58 (SD 1.75). Relapsing-remitting MS was most common (68/92, 74%), followed by secondary progressive (15/92, 16%) and primary progressive (9/92, 10%) courses. Pearson correlation analyses indicated significantly strong correlations for VSM, VM, SF, and IPS (all P<.001), with r values ranging from 0.58 to 0.78 for all cognitive domains. Test-retest reliability of the mHealth app was excellent (ICCs>0.90) for VM and IPS and good for VSM and SF (ICCs>0.80). Moreover, the SUS score averaged 84.5 (SD 13.34), and the mean total MAUQ score was 104.02 (SD 17.69), suggesting that DIGICOG-MS was highly usable and well appreciated.
CONCLUSIONS
The DIGICOG-MS tests were strongly correlated with traditional paper-based evaluations. Furthermore, people with MS positively evaluated DIGICOG-MS, finding it highly usable. Since cognitive impairment poses major limitations for people with MS, these findings open new paths to deploy digital cognitive tests for MS and further support the use of a novel mHealth app for cognitive self-assessment by people with MS in clinical practice.
PubMed: 38900535
DOI: 10.2196/56074 -
Science Advances Jun 2024Realizing a multifunctional integrated photonic platform is one of the goals for future optical information processing, which usually requires large size to realize due...
Realizing a multifunctional integrated photonic platform is one of the goals for future optical information processing, which usually requires large size to realize due to multiple integration challenges. Here, we realize a multifunctional integrated photonic platform with ultracompact footprint based on inverse design. The photonic platform is compact with 86 inverse designed-fixed couplers and 91 phase shifters. The footprint of each coupler is 4 μm by 2 μm, while the whole photonic platform is 3 mm by 0.2 mm-one order of magnitude smaller than previous designs. One-dimensional Floquet Su-Schrieffer-Heeger model and Aubry-André-Harper model are performed with measured fidelities of 97.90 (±0.52) % and 99.34 (±0.44) %, respectively. We also demonstrate a handwritten digits classification task with the test accuracy of 87% using on-chip training. Moreover, the scalability of this platform has been proved by demonstrating more complex computing tasks. This work provides an effective method to realize an ultrasmall integrated photonic platform.
PubMed: 38896615
DOI: 10.1126/sciadv.adm7569 -
Human Brain Mapping Jun 2024Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS)...
Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS) is related to increased tissue loss. The use of mcDESPOT (multicomponent driven single pulse observation of T1 and T2), a 3D imaging method which exploits both the T1 and T2 contrasts, allows FWF to be derived in clinically feasible times. However, this method has not been used to quantify changes of FWF and their potential clinical impact in MS. The aim of this study is to investigate the changes in FWF in MS patients and their relationship with tissue damage and cognition, under the hypothesis that FWF is a proxy of clinically meaningful tissue loss. To this aim, we tested the relationship between FWF, MS lesion burden and information processing speed, evaluated via the Symbol Digit Modalities Test (SDMT). In addition to standard sequences, used for T1- and T2-weighted lesion delineation, the mcDESPOT sequence with 1.7 mm isotropic resolution and a diffusion weighted imaging protocol (b = 0, 1200 s/mm, 40 diffusion directions) were employed at 3 T. The fractional anisotropy map derived from diffusion data was used to define a subject-specific white matter (WM) atlas. Brain parenchyma segmentation returned masks of gray matter (GM) and WM, and normal-appearing WM (NAWM), in addition to the T1 and T2 lesion masks (T1L and T2L, respectively). Ninety-nine relapsing-remitting MS patients (age = 43.3 ± 9.9 years, disease duration 12.3 ± 7.7 years) were studied, together with twenty-five healthy controls (HC, age = 38.8 ± 11.0 years). FWF was higher in GM and NAWM of MS patients, compared to GM and WM of HC (both p < .001). In MS patients, FWF was the highest in the T1L and GM, followed by T2L and NAWM, respectively. FWF increased significantly with T1L and T2L volume (ρ ranging from 0.40 to 0.58, p < .001). FWF in T2L was strongly related to both T1L volume and the volume ratio T1L/T2L (ρ = 0.73, p < .001). MS patients performed worse than HC in the processing speed test (mean ± SD: 54.1 ± 10.3 for MS, 63.8 ± 10.8 for HC). FWF in GM, T2L, perilesional tissue and NAWM increased with SDMT score reduction (ρ = -0.30, -0.29, -0.33 respectively and r = -.30 for T2L, all with p < .005). A regional analysis, conducted to determine which NAWM regions were of particular importance to explain the relationship between FWF and cognitive impairment, revealed that FWF spatial variance was negatively related to SDMT score in the corpus callosum and the superior longitudinal fasciculus, WM structures known to be associated with cognitive impairment, in addition to the left corticospinal tract, the sagittal stratum, the right anterior limb of internal capsule. In conclusion, we found excess free water in brain parenchyma of MS patients, an alteration that involved not only MS lesions, but also the GM and NAWM, impinging on brain function and negatively associated with cognitive processing speed. We suggest that the FWF metric, derived from noninvasive, rapid MRI acquisitions and bearing good biological interpretability, may prove valuable as an MRI biomarker of tissue damage and associated cognitive impairment in MS.
Topics: Humans; Female; Male; Adult; Middle Aged; Brain; Multiple Sclerosis; Diffusion Magnetic Resonance Imaging; Water; Cognitive Dysfunction; Parenchymal Tissue; White Matter; Gray Matter; Processing Speed
PubMed: 38895882
DOI: 10.1002/hbm.26761 -
Frontiers in Digital Health 2024To introduce MexOMICS, a Mexican Consortium focused on establishing electronic databases to collect, cross-reference, and share health-related and omics data on the...
OBJECTIVE
To introduce MexOMICS, a Mexican Consortium focused on establishing electronic databases to collect, cross-reference, and share health-related and omics data on the Mexican population.
METHODS
Since 2019, the MexOMICS Consortium has established three electronic-based registries: the Mexican Twin Registry (TwinsMX), Mexican Lupus Registry (LupusRGMX), and the Mexican Parkinson's Research Network (MEX-PD), designed and implemented using the Research Electronic Data Capture web-based application. Participants were enrolled through voluntary participation and on-site engagement with medical specialists. We also acquired DNA samples and Magnetic Resonance Imaging scans in subsets of participants.
RESULTS
The registries have successfully enrolled a large number of participants from a variety of regions within Mexico: TwinsMX ( = 2,915), LupusRGMX ( = 1,761) and MEX-PD ( = 750). In addition to sociodemographic, psychosocial, and clinical data, MexOMICS has collected DNA samples to study the genetic biomarkers across the three registries. Cognitive function has been assessed with the Montreal Cognitive Assessment in a subset of 376 MEX-PD participants. Furthermore, a subset of 267 twins have participated in cognitive evaluations with the Creyos platform and in MRI sessions acquiring structural, functional, and spectroscopy brain imaging; comparable evaluations are planned for LupusRGMX and MEX-PD.
CONCLUSIONS
The MexOMICS registries offer a valuable repository of information concerning the potential interplay of genetic and environmental factors in health conditions among the Mexican population.
PubMed: 38895515
DOI: 10.3389/fdgth.2024.1344103 -
Frontiers in Digital Health 2024The Research Program (Program) is an ongoing epidemiologic cohort study focused on collecting lifestyle, health, socioeconomic, environmental, and biological data from...
INTRODUCTION
The Research Program (Program) is an ongoing epidemiologic cohort study focused on collecting lifestyle, health, socioeconomic, environmental, and biological data from 1 million US-based participants. The Program has a focus on enrolling populations that are underrepresented in biomedical research (UBR). Federally Qualified Health Centers (FQHCs) are a key recruitment stream of UBR participants. The Program is digital by design where participants complete surveys via web-based platform. As many FQHC participants are not digitally ready, recruitment and retention is a challenge, requiring high-touch methods. However, high-touch methods ceased as an option in March 2020 when the Program paused in-person activities because of the pandemic. In January 2021, the Program introduced Computer Assisted Telephone Interviewing (CATI) to help participants complete surveys remotely. This paper aims to understand the association between digital readiness and mode of survey completion (CATI vs. web-based platform) by participants at FQHCs.
METHODS
This study included 2,089 participants who completed one or more surveys via CATI and/or web-based platform between January 28, 2021 (when CATI was introduced) and January 27, 2022 (1 year since CATI introduction).
RESULTS AND DISCUSSION
Results show that among the 700 not-digitally ready participants, 51% used CATI; and of the 1,053 digitally ready participants, 30% used CATI for completing retention surveys. The remaining 336 participants had "Unknown/Missing" digital readiness of which, 34% used CATI. CATI allowed survey completion over the phone with a trained staff member who entered responses on the participant's behalf. Regardless of participants' digital readiness, median time to complete retention surveys was longer with CATI compared to web. CATI resulted in fewer skipped responses than the web-based platform highlighting better data completeness. These findings demonstrate the effectiveness of using CATI for improving response rates in online surveys, especially among populations that are digitally challenged. Analyses provide insights for NIH, healthcare providers, and researchers on the adoption of virtual tools for data collection, telehealth, telemedicine, or patient portals by digitally challenged groups even when in-person assistance continues to remain as an option. It also provides insights on the investment of staff time and support required for virtual administration of tools for health data collection.
PubMed: 38895514
DOI: 10.3389/fdgth.2024.1379290 -
Digital Health 2024Telenursing e-learning courses have been shown to enhance nurses' skills and knowledge; however, the subjective learning experience is unclear. In this study, we...
OBJECTIVE
Telenursing e-learning courses have been shown to enhance nurses' skills and knowledge; however, the subjective learning experience is unclear. In this study, we identified meta-inferences to quantitatively and qualitatively understand this experience, as well as the types of knowledge gained through an e-learning course and how they are linked to each other, in order to enhance nurses' confidence in their understanding of telenursing.
METHODS
We employed a single-arm intervention with a mixed-methods convergent parallel design. We converged participants' self-reported pre- and post-course confidence scores with their reflections on the learning experience, which were reported qualitatively as improved or unimproved. A total of 143 Japanese nurses with a mean of 20 years of nursing experience participated in this study.
RESULTS
Among the participants, 72.7% demonstrated improved confidence in their understanding of telenursing after completing the e-learning course. The baseline confidence score was originally higher in the group that reported unimproved confidence (p < .001). Although there was no statistical difference in the usability and practicality scores between the two groups, the qualitative learning experience in these aspects differed in terms of the depth of knowledge of telenursing obtained.
CONCLUSIONS
Nurses' quantitative confidence in their understanding of telenursing after course completion was incongruent with their qualitative perspectives of the learning experience. Nursing educators, healthcare policymakers, and other stakeholders should consider that learners' overconfidence in their understanding of telenursing and comprehension of e-learning materials may result in their failure to develop key telenursing competencies, skills, and knowledge.
PubMed: 38894946
DOI: 10.1177/20552076241257034 -
Digital Health 2024Digital health interventions for behaviour change are usually complex interventions, and intervention developers should 'articulate programme theory', that is, they...
OBJECTIVE
Digital health interventions for behaviour change are usually complex interventions, and intervention developers should 'articulate programme theory', that is, they should offer detailed descriptions of individual intervention components and their proposed mechanisms of action. However, such detailed descriptions often remain lacking. The objective of this work was to provide a conceptual case study with an applied example of 'articulating programme theory' for a newly developed digital health intervention.
METHODS
Intervention Mapping methodology was applied to arrive at a detailed description of programme theory for a newly developed digital health intervention that aims to support cardiac rehabilitation patients in establishing heart-healthy physical activity habits. Based on a Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation (PRECEDE) logic model of the problem, a logic model of change was developed. The proposed mechanisms of action were visualised in an acyclic behaviour change diagram.
RESULTS
Programme theory for this digital health intervention includes 4 sub-behaviours of the main target behaviour (i.e. habitual heart-healthy physical activity), 8 personal determinants and 12 change objectives (i.e. changes needed at the determinant level to achieve the sub-behaviours). These are linked to 12 distinct features of the digital health intervention and 12 underlying behaviour change methods.
CONCLUSIONS
This case study offers a worked example of articulating programme theory for a digital health intervention using Intervention Mapping. Intervention developers and researchers may draw on this example to replicate the method, or to reflect on most suitable approaches for their own behaviour change interventions.
PubMed: 38894945
DOI: 10.1177/20552076241260974 -
Digital Health 2024Individuals increasingly turn to the Internet for health information, with YouTube being a prominent source. However, the quality and reliability of the health...
BACKGROUND
Individuals increasingly turn to the Internet for health information, with YouTube being a prominent source. However, the quality and reliability of the health information vary widely, potentially affecting health literacy and behavioural intentions.
METHODS
To analyse the impact of health information quality on health literacy and behavioural intention, we conducted a randomized controlled trial using a quality-controlled YouTube intervention. Health information quality on YouTube was evaluated using the Global Quality Score and DISCERN. We randomly allocated (1 : 1) to the intervention group to watch the highest quality-evaluated content and to the control group to watch the lowest quality-evaluated content. Health literacy and health behavioural intention were assessed before and after watching YouTube. The trial was set for two different topics: interpreting laboratory test results from health check-up and information about inflammatory bowel disease (IBD).
RESULTS
From 8 April 2022 to 15 April 2022, 505 participants were randomly assigned to watch either high-quality content (intervention group, n = 255) or low-quality content (control group, n = 250). Health literacy significantly improved in the intervention group (28.1 before and 31.8 after; < 0.01 for health check-up; 28.3 before and 31.3 after; < 0.01 for IBD). Health behavioural intention significantly improved in the intervention group (3.5 before and 4.1 after; < 0.01 for health check-up; 3.6 before and 4.0 after; < 0.01 for IBD). Control groups had no such effect.
CONCLUSION
High-quality health information can enhance health literacy and behavioural intention in both healthy individuals and those with specific conditions like IBD. It stresses the significance of ensuring reliable health information online and calls for future efforts to curate and provide access to high-quality health content.
PubMed: 38894944
DOI: 10.1177/20552076241263691