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Background: Health care systems in low- and middle-income countries (LMICs) can greatly benefit from artificial intelligence (AI) interventions in various use cases such as diagnostics, treatment, and public health monitoring but face significant challenges in sharing data for developing and deploying AI in health care., Objective: This study aimed to identify barriers and enablers to data sharing for AI in health care in LMICs and to test the relevance of these in a local context., Methods: First, we conducted a systematic literature search using PubMed, SCOPUS, Embase, Web of Science, and ACM using controlled vocabulary. Primary research studies, perspectives, policy landscape analyses, and commentaries performed in or involving an LMIC context were included. Studies that lacked a clear connection to health information exchange systems or were not reported in English were excluded from the review. Two reviewers independently screened titles and abstracts of the included articles and critically appraised each study. All identified barriers and enablers were classified according to 7 categories as per the predefined framework-technical, motivational, economic, political, legal and policy, ethical, social, organisational, and managerial. Second, we tested the local relevance of barriers and enablers in Thailand through stakeholder interviews with 15 academic experts, technology developers, regulators, policy makers, and health care providers. The interviewers took notes and analyzed data using framework analysis. Coding procedures were standardized to enhance the reliability of our approach. Coded data were reverified and themes were readjusted where necessary to avoid researcher bias., Results: We identified 22 studies, the majority of which were conducted across Africa (n=12, 55%) and Asia (n=6, 27%). The most important data-sharing challenges were unreliable internet connectivity, lack of equipment, poor staff and management motivation, uneven resource distribution, and ethical concerns. Possible solutions included improving IT infrastructure, enhancing funding, introducing user-friendly software, and incentivizing health care organizations and personnel to share data for AI-related tools. In Thailand, inconsistent data systems, limited staff time, low health data literacy, complex and unclear policies, and cybersecurity issues were important data-sharing challenges. Key solutions included building a conducive digital ecosystem-having shared data input platforms for health facilities to ensure data uniformity and to develop easy-to-understand consent forms, having standardized guidelines for data sharing, and having compensation policies for data breach victims., Conclusions: Although AI in LMICs has the potential to overcome health inequalities, these countries face technical, political, legal, policy, and organizational barriers to sharing data, which impede effective AI development and deployment. When tested in a local context, most of these barriers were relevant. Although our findings might not be generalizable to other contexts, this study can be used by LMICs as a framework to identify barriers and strengths within their health care systems and devise localized solutions for enhanced data sharing., Trial Registration: PROSPERO CRD42022360644; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=360644., (©Aprajita Kaushik, Capucine Barcellona, Nikita Kanumoory Mandyam, Si Ying Tan, Jasper Tromp. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 04.02.2025.)

Background: Existing research on health equity falls short of identifying a comprehensive set of indicators for measurement across health systems. Health systems in the ASEAN region, in particular, lack a standardised framework to assess health equity. This paper proposes a comprehensive framework to measure health equity in the ASEAN region and highlights current gaps in data availability according to its indicator components., Methods: A comprehensive literature review was undertaken to map out a core set of indicators to evaluate health equity at the health system level. Secondary data collection was subsequently conducted to assess current data availability for ASEAN states in key global health databases, national health accounts, and policy documents., Results: A robust framework to measure health equity was developed comprising 195 indicators across Health System Inputs and Processes, Outputs, Outcomes, and Contextual Factors. Total indicator data availability equated to 72.9% (1423/1950). Across the ASEAN region, the Inputs and Processes sub-component of Health Financing had complete data availability for all indicators (160/160, 100%), while Access to Essential Medicine had the least data available (6/30, 20%). Under Outputs and Outcomes, Coverage of Selected Interventions (161/270, 59.63%) and Population Health (350/350, 100%) respectively had the most data available, while other indicator sub-components had little to none (≤ 38%). 72.145% (384/530) of data is available for all Contextual Factors. Out of the 10 ASEAN countries, the Philippines had the highest data availability overall at 77.44% (151/195), while Brunei Darussalam and Vietnam had the lowest data availability at 67.18% (131/195)., Conclusions: The data availability gaps highlighted in this study underscore the need for a standardised framework to guide data collection and benchmarking of health equity in ASEAN. There is a need to prioritise regular data collection for overlooked indicator areas and in countries with low levels of data availability. The application of this indicator framework and resulting data availability analysis could be conducted beyond ASEAN to enable cross-regional benchmarking of health equity., (© 2023. The Author(s).)

Competing Interests: No conflicts to declare.

There are ethical obligations to conduct research that contributes to generalisable knowledge and improves reproductive health, and this should include embryo research in jurisdictions where it is permitted. Often, the controversial nature of embryo research can alarm ethics committee members, which can unnecessarily delay important research that can potentially improve fertility for patients and society. Such delay is ethically unjustified. Moreover, countries such as the UK, Australia and Singapore have legislation which unnecessarily captures low-risk research, such as observational research, in an often cumbersome and protracted review process. Such countries should revise such legislation to better facilitate low-risk embryo research.We introduce a philosophical distinction to help decision-makers more efficiently identify higher risk embryo research from that which presents no more risks to persons than other types of tissue research. That distinction is between future person embryo research and non-future person embryo research. We apply this distinction to four examples of embryo research that might be presented to ethics committees.Embryo research is most controversial and deserving of detailed scrutiny when it potentially affects a future person. Where it does not, it should generally require less ethical scrutiny. We explore a variety of ways in which research can affect a future person, including by deriving information about that person, and manipulating eggs or sperm before an embryo is created., Competing Interests: Competing interests: JS, through his involvement with the Murdoch Children’s Research Institute, received funding through from the Victorian State Government through the Operational Infrastructure Support (OIS) Program. JS is a partner investigator on an Australian Research Council Linkage award (LP190100841, October 2020–2023) which involves industry partnership from Illumina. He does not personally receive or control any funds from Illumina. He presented at a Genomic Prediction-organised webinar (2021), but received no payment or other benefits from Genomic Prediction. He is a Bioethics Committee consultant for Bayer. No other COIs., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Optical remote sensors are nowadays ubiquitously used, thanks to unprecedented advances in the last decade in photonics, machine learning and signal processing tools. In this work we study experimentally the remote recovery of audio signals from the silent videos of the movement of optical speckle patterns. This technique can be used even when in between the source and the receiver there is a medium that does not allow for the propagation of sound waves. We use a diode laser to generate a speckle pattern on the membrane of a loudspeaker and a low-cost CCD camera to record the video of the movement of the speckle pattern when the loudspeaker plays an audio signal. We perform a comparative analysis of six signal recovery algorithms. In spite of having different complexity and computational requirements, we find that the algorithms have (except for the simplest one) good performance in terms of the quality of the recovered signal. The best trade-off, in terms of computational costs and performance, is obtained with a new method that we propose, which recovers the signal from the weighted sum of the intensities of all the pixels, where the signs of the weights are determined by selecting a reference pixel and calculating the signs of the cross-correlations of the intensity of the reference pixel and the intensities of the other pixels.

Background: No oral systemic treatments are approved for pediatric patients with psoriasis., Objective: To evaluate the pharmacokinetics and safety of apremilast, an oral phosphodiesterase 4 inhibitor, in pediatric patients with psoriasis., Methods: This phase 2, multicenter, open-label study enrolled pediatric patients with moderate to severe plaque psoriasis. Patients received apremilast twice daily without titration for 2 weeks (group 1 [age, 12-17 years; weight, ≥35 kg]: apremilast 20 or 30 mg; group 2 [age, 6-11 years; weight, ≥15 kg]: apremilast 20 mg), followed by a 48-week extension. Primary endpoints were pharmacokinetics and safety. Other endpoints were taste/acceptability and change from baseline in score on the Psoriasis Area and Severity Index., Results: A total of 42 enrolled patients (21 adolescents [age, 12-17 years] and 21 children [age, 6-11 years]) received apremilast. Pharmacokinetics modeling and noncompartmental analyses showed that weight-based dosing with apremilast 20 mg twice daily in children or apremilast 20 or 30 mg twice daily in adolescents provides exposure (area under the concentration-time curve from time 0 to 12 hours after the dose) that is comparable to that achieved with apremilast 30 mg twice daily in adults. The safety profile was generally similar to that in adults. Most study participants liked the taste of the tablet. Improvements from baseline in mean Psoriasis Area and Severity Index score were 68% for adolescents (overall) and 79% for children., Limitations: No children weighing less than 20 kg were enrolled., Conclusions: This first-time-in-children phase 2 study supports weight-based apremilast dosing for future phase 3 studies of pediatric plaque psoriasis., (Copyright © 2019 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Hereditary transthyretin amyloidosis (hATTR) is a life-threatening multisystemic disease with sensory-motor peripheral neuropathy, cardiomyopathy and dysautonomia. Although the six-minute walk test (6MWT) is one of the most popular clinical tests to assess functional exercise capacity in cardiopulmonary and neuromuscular diseases, little is known about 6MWT in evaluating hATTR patients. A prospective single-center pilot study was performed in twenty hATTR patients, comparing 6MWT with widely used outcome measures. After 18 months, fourteen patients were re-evaluated. 6MWT performance was highly related with familial amyloidotic polyneuropathy stage and polyneuropathy disability score, and with CMT examination score, neuropathy impairment score-lower limbs and Kumamoto score. There was no correlation with compound autonomic dysfunction test, modified body mass index and numerous indices of heart dysfunction. After 18 months, familial amyloidotic polyneuropathy stage and polyneuropathy disability score systems were not able to reveal any significant change, whereas all other outcome measures significantly worsened. Among the outcome measures monitoring the neuropathic disturbances, neuropathy impairment score-lower limbs showed the highest responsiveness to change (adjusted effect size: 0.79), followed by CMT examination score (0.67), Kumamoto scale (0.65), 6MWT (0.62). 10MWT showed a very small value (0.21). Compound autonomic dysfunction test had a large value (0.91) whereas modified body mass index a small/moderate value (0.49). 6MWT is a simple and sensitive tool to monitor neuropathic involvement but not cardiac dysfunction in hATTR course., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

In Duchenne muscular dystrophy (DMD) little has been reported on the association between clinical outcome measures and patient health-related quality of life (HRQOL) tools. Our study evaluated the relationship between 12 month changes on the Generic Core Scales (GCS), the Multidimensional Fatigue Scale and the Neuromuscular Module of the PedsQL(TM) with several outcome measures (6 minute walk test, North Star Ambulatory Assessment and timed items) in ambulatory DMD. Ninety-eight ambulatory DMD in a multicentric setting were included in the study. At baseline, the PedsQL(TM) inventories correlated with almost all the functional measures On the Child Self-Report there was a significant decrease between baseline and 12 months on the PedsQL(TM) GCS and its first domain, in parallel with the decrement in the functional outcome measures. Correlation between the 12 month changes on the PedsQL(TM) inventories and functional measures were almost all negligible. Similar results were obtained on the Parent Proxy-Report. In conclusion, PedsQL(TM) correlates with the level of impairment at baseline, but this does not hold true when 12 month changes are considered. Further studies comparing different tools are needed to better elucidate the complexity of the relationship between HRQOL and functional performances., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)