Category: Statistics

Proc Natl Acad Sci U S A. 2023 Feb 28;120(9):e2218375120. doi: 10.1073/pnas.2218375120. Epub 2023 Feb 23.

ABSTRACT

The recent increase in openly available ancient human DNA samples allows for large-scale meta-analysis applications. Trans-generational past human mobility is one of the key aspects that ancient genomics can contribute to since changes in genetic ancestry-unlike cultural changes seen in the archaeological record-necessarily reflect movements of people. Here, we present an algorithm for spatiotemporal mapping of genetic profiles, which allow for direct estimates of past human mobility from large ancient genomic datasets. The key idea of the method is to derive a spatial probability surface of genetic similarity for each individual in its respective past. This is achieved by first creating an interpolated ancestry field through space and time based on multivariate statistics and Gaussian process regression and then using this field to map the ancient individuals into space according to their genetic profile. We apply this algorithm to a dataset of 3138 aDNA samples with genome-wide data from Western Eurasia in the last 10,000 y. Finally, we condense this sample-wise record with a simple summary statistic into a diachronic measure of mobility for subregions in Western, Central, and Southern Europe. For regions and periods with sufficient data coverage, our similarity surfaces and mobility estimates show general concordance with previous results and provide a meta-perspective of genetic changes and human mobility.

PMID:36821583 | DOI:10.1073/pnas.2218375120

PLoS One. 2023 Feb 23;18(2):e0282082. doi: 10.1371/journal.pone.0282082. eCollection 2023.

ABSTRACT

OBJECTIVE: This study aimed to enable the automatic detection of the hippocampus and diagnose mesial temporal lobe epilepsy (MTLE) with the hippocampus as the epileptogenic area using artificial intelligence (AI). We compared the diagnostic accuracies of AI and neurosurgical physicians for MTLE with the hippocampus as the epileptogenic area.

METHOD: In this study, we used an AI program to diagnose MTLE. The image sets were processed using a code written in Python 3.7.4. and analyzed using Open Computer Vision 4.5.1. The deep learning model, which was a fine-tuned VGG16 model, consisted of several layers. The diagnostic accuracies of AI and board-certified neurosurgeons were compared.

RESULTS: AI detected the hippocampi automatically and diagnosed MTLE with the hippocampus as the epileptogenic area on both T2-weighted imaging (T2WI) and fluid-attenuated inversion recovery (FLAIR) images. The diagnostic accuracies of AI based on T2WI and FLAIR data were 99% and 89%, respectively, and those of neurosurgeons based on T2WI and FLAIR data were 94% and 95%, respectively. The diagnostic accuracy of AI was statistically higher than that of board-certified neurosurgeons based on T2WI data (p = 0.00129).

CONCLUSION: The deep learning-based AI program is highly accurate and can diagnose MTLE better than some board-certified neurosurgeons. AI can maintain a certain level of output accuracy and can be a reliable assistant to doctors.

PMID:36821567 | DOI:10.1371/journal.pone.0282082

JMIR Pediatr Parent. 2023 Feb 23;6:e43814. doi: 10.2196/43814.

ABSTRACT

BACKGROUND: Monitoring ocular morbidity among pediatric patients requires regular follow-up visits. We found that the follow-up rate was poor among children in our setting. Therefore, we intended to assess the effectiveness of 2 interventions-(1) counseling and (2) SMS text messaging and phone calls-to improve the follow-up rates.

OBJECTIVE: This study aimed to evaluate the effectiveness of 2 interventions, counseling and SMS and phone calls group, as well as a routine standard care for improving the follow-up rate of pediatric patients.

METHODS: A Nonrandomized, quasiexperimental design was used. Children (aged 0-16 years) with ocular conditions requiring at least 3 follow-up visits during the study period were included. A total of 264 participants were equally allocated to the 3 intervention groups of (1) counseling, (2) SMS and phone calls, and (3) routine standard care group. A 20-minute counseling session by a trained counselor with the provision of disease-specific leaflets were given to those in the counseling group. For the second intervention group, parents of children received an SMS text 3 days before and a phone call 1 day before their scheduled follow-up visits. Participants allocated for the routine standard care group were provided with the existing services with no additional counseling and reminders. Participants attending 3 follow-ups within 2 days of the scheduled visit date were considered compliant. The difference in and among the proportion of participants completing all 3 follow-up visits in each group was assessed.

RESULTS: The demographic characteristics of the participants were similar across the study groups. Only 3% (8/264) of participants completed all 3 follow-up visits, but overall compliance with the follow-up, as defined by the investigators, was found to be only 0.76% (2/264). There was no statistically significant difference in the proportion of follow-up between the intervention groups. However, the proportion of participants attending the first and second follow-ups, as well as the overall total number of follow-ups, was more in the SMS and phone-call group followed by the counseling group.

CONCLUSIONS: We did not find any evidence on the effectiveness of our interventions to improve the follow-up rate. The primary reason could be that this study was conducted during the COVID-19 pandemic. It could also be possible that the intensity of the interventions may have influenced the outcomes. A rigorously designed study during the absence of any lockdown restrictions is warranted to evaluate intervention effectiveness. The study also provides useful insights and highlights the importance of designing and systematically developing interventions for improving the follow-up rate and ensuring a continuum of care to children with visual disabilities in Nepal and similar contexts.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04837534; https://clinicaltrials.gov/ct2/show/NCT04837534.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/31578.

PMID:36821366 | DOI:10.2196/43814

JMIR Form Res. 2023 Feb 23;7:e37987. doi: 10.2196/37987.

ABSTRACT

BACKGROUND: Black women in college are disproportionately affected by HIV diagnoses. Mobile apps can facilitate the innovative delivery of accurate HIV and sexual and reproductive health information. However, mobile health interventions are severely underused in this population.

OBJECTIVE: We aimed to quantitatively and qualitatively explore the perspectives of college-aged Black women on using a mobile health app for HIV prevention and sexual and reproductive health. The data obtained from Black women were used to design preliminary mobile app wireframes and features.

METHODS: This explanatory, sequential mixed methods study took place from 2019 to 2020 and targeted Black women who were enrolled in college or who had recently graduated from college. Convenience sampling was used during the quantitative phase, followed by purposive sampling in the qualitative phase. A cross-sectional web-based survey evaluating the willingness to use a mobile app for HIV prevention was conducted in the quantitative phase. Descriptive statistics were used for all variables. A separate focus group discussion was conducted with Black women in college to expand on the quantitative results. Focus group discussions explored their perceptions on HIV and health content delivered through a mobile app along with potential features that participants desired within the app. Using the data obtained, we selected the primary features for the app prototype.

RESULTS: In total, we enrolled 34 participants in the survey, with 6 participating in focus group discussions. Over half of the respondents reported a willingness to use an app that contained pre-exposure prophylaxis content. Women who claimed recent sexual activity reported being more likely to use an app feature that would allow them to order an at-home HIV testing kit than their non-sexually active counterparts. The emerging themes from the focus group session were Black women’s health concerns, HIV risk, sources of health information, and preferred app features. The content in our prototype included speaking with a specialist, HIV and pre-exposure prophylaxis information, holistic wellness, and features promoting engagement and retention.

CONCLUSIONS: The results of our study guided the design of wireframes for an app prototype targeting HIV prevention in college-aged Black women. The rapid growth of mobile devices in Black communities, coupled with high rates of smartphone ownership among Black youth, makes mobile health interventions a promising strategy for addressing sexual and reproductive health disparities. Participants in our sample were willing to use a culturally appropriate and gender-considerate app for their sexual health needs. Our findings indicate that Black women in college may be excellent candidates for mobile app-based interventions.

PMID:36821362 | DOI:10.2196/37987

JMIR Form Res. 2023 Feb 23;7:e42881. doi: 10.2196/42881.

ABSTRACT

BACKGROUND: The Connecting2gether (C2) platform is a web and mobile-based information-sharing tool that aims to improve care for children with medical complexity and their families. A key feature of C2 is secure messaging, which enables parental caregivers (PCs) to communicate with their child’s care team members (CTMs) in a timely manner.

OBJECTIVE: The objectives of this study were to (1) evaluate the use of a secure messaging system, (2) examine and compare the content of messages to email and phone calls, and (3) explore PCs’ and CTMs’ perceptions and experiences using secure messaging as a method of communication.

METHODS: This is a substudy of a larger feasibility evaluation of the C2 platform. PCs of children with medical complexity were recruited from a tertiary-level complex care program to use the C2 platform for 6 months. PCs could invite CTMs involved in their child’s care to register on the platform. Messages were extracted from C2, and phone and email data were extracted from electronic medical records. Quantitative data from the use of C2 were analyzed using descriptive statistics. Messaging content codes were iteratively developed through a review of the C2 messages and phone and email communication. Semistructured interviews were completed with PCs and CTMs. Communication and interview data were analyzed using thematic analysis.

RESULTS: A total of 36 PCs and 66 CTMs registered on the C2 platform. A total of 1861 messages were sent on C2, with PCs and nurse practitioners sending a median of 30 and 74 messages, respectively. Of all the C2 messages, 85.45% (1257/1471) were responded to within 24 hours. Email and phone calls focused primarily on clinical concerns and medications, whereas C2 messaging focused more on parent education, proactive check-ins, and nonmedical aspects of the child’s life. Four themes emerged from the platform user interviews related to C2 messaging: (1) connection to the care team, (2) efficient communication, (3) clinical uses of secure messaging, and (4) barriers to use.

CONCLUSIONS: Overall, our study provides valuable insight into the benefits of secure messaging in the care of children with medical complexity. Secure messaging provided the opportunity for continued family teaching, proactive check-ins from health care providers, and casual conversations about family and child life, which contributed to PCs feeling an improved sense of connection with their child’s health care team. Secure messaging can be a beneficial additional communication method to improve communication between PCs and their care team, reducing the associated burden of care coordination and ultimately enhancing the experience of care delivery. Future directions include the evaluation of secure messaging when integrated into electronic medical records, as this has the potential to work well with CTM workflow, reduce redundancy, and allow for new features of secure messaging.

PMID:36821356 | DOI:10.2196/42881

JMIR Mhealth Uhealth. 2023 Feb 23;11:e40416. doi: 10.2196/40416.

ABSTRACT

BACKGROUND: In contrast to the large and increasing number of patients with stroke, clinical rehabilitation resources cannot meet their rehabilitation needs. Especially for those discharged, ways to carry out effective rehabilitation training without the supervision of physicians and receive guidance from physicians remain urgent problems to be solved in clinical rehabilitation and have become a research hot spot at home and abroad. At present, there are many studies on home rehabilitation training based on wearable devices, Kinect, among others, but these have disadvantages (eg, complex systems, high price, and unsatisfactory rehabilitation effects).

OBJECTIVE: This study aims to design a remote intelligent rehabilitation training system based on wearable devices and human-computer interaction training tasks, and to evaluate the effectiveness and safety of the remote rehabilitation training system for nonphysician-supervised motor rehabilitation training of patients with stroke through a clinical trial study.

METHODS: A total of 120 inpatients with stroke having limb motor dysfunction were enrolled via a randomized, parallel-controlled method in the rehabilitation institutions, and a 3-week clinical trial was conducted in the rehabilitation hall with 60 patients in the experimental group and 60 in the control group. The patients in the experimental group used the remote rehabilitation training system for rehabilitation training and routine clinical physical therapy (PT) training and received routine drug treatment every day. The patients in the control group received routine clinical occupational therapy (OT) training and routine clinical PT training and routine drug treatment every day. At the beginning of the training (baseline) and after 3 weeks, the Fugl-Meyer Motor Function Rating scale was scored by rehabilitation physicians, and the results were compared and analyzed.

RESULTS: Statistics were performed using SAS software (version 9.4). The total mean Fugl-Meyer score improved by 11.98 (SD 8.46; 95% CI 9.69-14.27) in the control group and 17.56 (SD 11.65; 95% CI 14.37-20.74) in the experimental group, and the difference between the 2 groups was statistically significant (P=.005). Among them, the mean Fugl-Meyer upper extremity score improved by 7.45 (SD 7.24; 95% CI 5.50-9.41) in the control group and 11.28 (SD 8.59; 95% CI 8.93-13.62) in the experimental group, and the difference between the 2 groups was statistically significant (P=.01). The mean Fugl-Meyer lower extremity score improved by 4.53 (SD 4.42; 95% CI 3.33-5.72) in the control group and 6.28 (SD 5.28; 95% CI 4.84-7.72) in the experimental group, and there was no significant difference between the 2 groups (P=.06). The test results showed that the experimental group was better than the control group, and that the patients’ motor ability was improved.

CONCLUSIONS: The remote rehabilitation training system designed based on wearable devices and human-computer interaction training tasks can replace routine clinical OT training. In the future, through medical device registration certification, the system will be used without the participation of physicians or therapists, such as in rehabilitation training halls, and in remote environments, such as communities and homes.

TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200061310; https://tinyurl.com/34ka2725.

PMID:36821348 | DOI:10.2196/40416

Appl Opt. 2023 Feb 20;62(6):A1-A11. doi: 10.1364/AO.473632.

ABSTRACT

Velocity measurement has a high application value in hydrological monitoring and flood disaster warning. The long-distance laser Doppler water flow velocimetry technology has the advantage of strong anti-interference ability and high spatial resolution, and it can realize the high-precision measurement of water flow velocity. Because water flow has low reflectance characteristics, how to extract Doppler frequency from weak non-stationary coherent signals is a crucial problem to be solved to realize long-distance water flow velocity measurement. However, the classical method requires the time domain signal to have high stationarity and is not suitable for processing the coherent signal in the water flow velocity measurement. Aiming at this problem, we proposed a water flow velocimetry method based on adaptive Gaussian weighted integral (AGWI). First, the spectral characteristics of the coherent signal are analyzed in detail, and a statistical model of weak non-stationary signals is established. A second-order Kaiser self-multiplication window (KSMW) is designed to suppress spectral leakage for the asynchronously sampled data. Then, an adaptive homogenization power spectral subtraction (AHPSS) is designed to reduce system noise. Finally, the Doppler spectrum reconstruction and Doppler frequency estimation are performed using the AGWI method to obtain the Doppler frequency, which is further processed to get the water flow velocity. The experimental results show that the method proposed in this paper can achieve accurate and stable measurement of river surface velocity under long-distance conditions.

PMID:36821294 | DOI:10.1364/AO.473632

Appl Opt. 2023 Feb 10;62(5):1253-1262. doi: 10.1364/AO.475825.

ABSTRACT

The fast-Fourier-transform-based filtering method for phase screen generation remains popular for numerical simulation of optical propagation through turbulence; however, these screens inherently underrepresent the spectral density at low wavenumbers. Here, the “Z-tilt” approach is explored to augment the spectral density at low wavenumbers by adding a random phase tilt, which is derived from the wavefront phase statistics of a Zernike polynomial basis. This approach is computationally efficient and can be applied to any statistically homogeneous and isotropic refractive index field. An analytic result is provided for the von Kármán spectrum with finite outer scale. In a quantitative comparison with phase screens compensated for using a common subharmonic approach, the Z-tilt method shows the best agreement with the analytical structure function when the outer scale is greater than about three times the screen dimension. For outer scales of the order of the screen dimension, the subharmonic and a modified Z-tilt method give the most accurate results. A propagation simulation demonstrates that the aperture-averaged angle-of-arrival variance is accurately predicted using the Z-tilt method.

PMID:36821225 | DOI:10.1364/AO.475825

J Opt Soc Am A Opt Image Sci Vis. 2023 Feb 1;40(2):285-293. doi: 10.1364/JOSAA.477639.

ABSTRACT

We show that quantum detector tomography can be applied to the human visual system to explore human perception of photon number states. In detector tomography, instead of using very hard-to-produce photon number states, the response of a detector to light pulses with known photon statistics of varying intensity is recorded, and a model is fitted to the experimental outcomes, thereby inferring the detector’s photon number state response. Generally, light pulses containing a Poisson-distributed number of photons are utilized, which are very easy to produce in the lab. This technique has not been explored to study the human visual system before because it usually requires a very large number of repetitions not suitable for experiments on humans. Yet, in the present study we show that detector tomography is feasible for human experiments. Assuming a simple model for this accuracy, the results of our simulations show that detector tomography is able to reconstruct the model using Bayesian inference with as few as 5000 trials. We then optimize the experimental parameters in order to maximize the probability of showing that the single-photon accuracy is above chance. As such, our study opens the road to study human perception on the quantum level.

PMID:36821198 | DOI:10.1364/JOSAA.477639

J Opt Soc Am A Opt Image Sci Vis. 2023 Feb 1;40(2):237-258. doi: 10.1364/JOSAA.472553.

ABSTRACT

Analysis of visual texture is important for many key steps in early vision. We study visual sensitivity to image statistics in three families of textures that include multiple gray levels and correlations in two spatial dimensions. Sensitivities to positive and negative correlations are approximately independent of correlation sign, and signals from different kinds of correlations combine quadratically. We build a computational model, fully constrained by prior studies of sensitivity to uncorrelated textures and black-and-white textures with spatial correlations. The model accounts for many features of the new data, including sign-independence, quadratic combination, and the dependence on gray-level distribution.

PMID:36821194 | DOI:10.1364/JOSAA.472553