Tag: statistics

IEEE J Biomed Health Inform. 2024 Dec 18;PP. doi: 10.1109/JBHI.2024.3519717. Online ahead of print.

ABSTRACT

Schizophrenia (SZ) is a severe mental disorder characterized by hallucinations, delusions, cognitive impairments, and social withdrawal. It leads to a series of brain abnormalities, particularly the deformation of the hippocampus and amygdala, which are highly associated with emotion, memory, and motivation. Most previous studies have used the hippocampal and amygdaloid volume, whereas surface-based morphometry reflects nuclear deformation more finely, but it is unclear the hippocampal and amygdaloid morphometry relates to schizophrenic pathology and its potential as a biomarker. In this study, we extracted individual multivariate morphometry statistics (MMS) of hippocampus and amygdala from MRI images and analyzed the morphometric differences between groups. After dictionary learning and max pooling, we obtain reduced dimensional features and use machine learning algorithms for individual diagnosis. The results showed that the hippocampus of the schizophrenia group was significantly atrophied bilaterally and the atrophied areas were symmetrical. Subregions of the amygdala are both atrophied and expanded, and in particular, the right amygdala shows a greater degree and extent of deformation. Using the random forest classifier, the accuracy of classification using hippocampal and amygdaloid morphometric features are 94.52% and 94.57%, respectively, and the accuracy of classification combining the two morphometric features reached 96.57%. Our study demonstrates the efficacy of MMS in identifying morphometric differences of the hippocampus and amygdala between healthy controls and schizophrenic, and these findings emphasize the potential of MMS as a reliable biomarker for the diagnosis of schizophrenia.

PMID:40030599 | DOI:10.1109/JBHI.2024.3519717

IEEE J Biomed Health Inform. 2024 Dec 25;PP. doi: 10.1109/JBHI.2024.3522485. Online ahead of print.

ABSTRACT

Event-Related Potentials (ERPs) studies are powerful and widespread tools in neuroscience. The standard pipeline foresees the individuation of relevant components, and the computation of discrete features characterizing them, as latency and amplitude. Nonetheless, this approach only evaluates one aspect of the signal at a time, without considering its overall morphology; consequently being highly susceptible to low signal to noise ratio. In this context, we resort to Functional Data Analysis: a statistical methodology designed for the examination of curves and functions. Treating functions as statistical units enables the extraction of features that encompass the complete signal morphology. Functional Principal Component Analysis addresses whole ERPs as statistical units, allowing for the extraction of interpretable and comprehensive features. Exploiting this method, we compute three functional features from ERPs registered during an image categorization task. To validate our approach, firstly we examine the correlation between functional and discrete features to address the amount of overlapping information, and we consider the consistency of the obtained insights with previous literature. Moreover, we assess the effectiveness of our method by evaluating the classification performance achieved when using our extracted features to identify the object observed during the ERP recording. Such performance is compared to state-of-the-art feature extraction methods, using multiple metrics, classification algorithms, and datasets. The functional features consistently perform better, or analogously, across metrics, algorithms, and datasets they also embed additional information and provide insights coherent with previous literature, proving the usefulness of Functional Data Analysis in the context of ERP studies.

PMID:40030597 | DOI:10.1109/JBHI.2024.3522485

IEEE J Biomed Health Inform. 2024 Dec 2;PP. doi: 10.1109/JBHI.2024.3509438. Online ahead of print.

ABSTRACT

Transcranial alternating current stimulation (tACS) has been reported to treat refractory auditory hallucinations in schizophrenia. Despite diligent efforts, it is imperative to underscore that tACS does not uniformly demonstrate efficacy across all patients as with all treatments currently employed in clinical practice. The study aims to find biomarkers predicting individual responses to tACS, guiding treatment decisions, and preventing healthcare resource wastage. We divided 17 schizophrenic patients with refractory auditory hallucinations into responsive(RE) and non-responsive(NR) groups based on their auditory hallucination symptom reduction rates after one month of tACS treatment. The pre-treatment resting-state electroencephalogram(rsEEG) was recorded and then computed absolute power spectral density (PSD), Hjorth parameters (HPs, Hjorth activity (HA), Hjorth mobility (HM), and Hjorth complexity (HC) included) from different frequency bands to portray the brain oscillations. The results demonstrated that statistically significant differences localized within the high gamma frequency bands of the right brain hemisphere. Immediately, we input the significant dissociable features into popular machine learning algorithms, the Cascade Forward Neural Network achieved the best recognition accuracy of 93.87%. These findings preliminarily imply that high gamma oscillations in the right brain hemisphere may be the main influencing factor leading to different responses to tACS treatment, and incorporating rsEEG signatures could improve personalized decisions for integrating tACS in clinical treatment.

PMID:40030555 | DOI:10.1109/JBHI.2024.3509438

IEEE Trans Neural Syst Rehabil Eng. 2024 Dec 2;PP. doi: 10.1109/TNSRE.2024.3510369. Online ahead of print.

ABSTRACT

The range of motion (ROM) of joints in the human body is essential for movement and functional performance. Real-time monitoring of joint angles is crucial for confirming pathologic biomechanics, providing feedback during rehabilitation, and evaluating the treatment efficacy. This study aims to evaluate the concurrent validity of a wearable nanocomposite strain sensor with a two-dimensional electrical goniometer and its repeatability for measuring knee ROM during repetitive joint movements in 10 healthy female participants. The participants performed seated knee flexion and extension in three sessions, during which knee ROM was measured simultaneously using the two devices. A statistical analysis was conducted using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. The strain sensor demonstrated excellent concurrent validity (ICC = 0.94) and good reliability (ICC = 0.87), with biases close to zero and the magnitude of disagreements lying within ±5-10° for validity and ±10-15° for reliability. The standard deviation of the mean (SEM) for absolute reliability was 2.18°, with the width of variability based on SEM at 9.88°. The results indicate that the strain sensor exhibits clinically acceptable accuracy and precision, comparable to the existing wearable sensors. However, careful interpretation is required for variations in repeated measurements exceeding 10°. Future research should focus on enhancing the sensor attachment and calibration methods, along with broadening the application scope to more dynamic activities, other joints, and patients with specific pathologies. The strain sensor presents significant potential for real-time and continuous monitoring of joint angles during real-world activities as well as rehabilitation programs.

PMID:40030545 | DOI:10.1109/TNSRE.2024.3510369

IEEE Trans Med Imaging. 2024 Dec 5;PP. doi: 10.1109/TMI.2024.3512175. Online ahead of print.

ABSTRACT

Cardiac imaging protocols usually result in several types of acquisitions and descriptors extracted from the images. The statistical analysis of such data across a population may be challenging, and can be addressed by fusion techniques within a dimensionality reduction framework. However, directly combining different data types may lead to unfair comparisons (for heterogeneous descriptors) or over-exploitation of information (for strongly correlated modalities). In contrast, physicians progressively consider each type of data based on hierarchies derived from their experience or evidence-based recommendations, an inspiring approach for data fusion strategies. In this paper, we propose a novel methodology for hierarchical data fusion and unsupervised representation learning. It mimics the physicians’ approach by progressively integrating different high-dimensional data descriptors according to a known hierarchy. We model this hierarchy with a Hierarchical Gaussian Process Latent Variable Model (GP-LVM), which links the estimated low-dimensional latent representation and high-dimensional observations at each level in the hierarchy, with additional links between consecutive levels of the hierarchy. We demonstrate the relevance of this approach on a dataset of 1726 magnetic resonance image slices from 123 patients revascularized after acute myocardial infarction (MI) (first level in the hierarchy), some of them undergoing reperfusion injury (microvascular obstruction (MVO), second level in the hierarchy). Our experiments demonstrate that our hierarchical model provides consistent data organization across levels of the hierarchy and according to physiological characteristics of the lesions. This allows more relevant statistical analysis of myocardial lesion patterns, and in particular subtle lesions such as MVO.

PMID:40030503 | DOI:10.1109/TMI.2024.3512175

IEEE J Biomed Health Inform. 2024 Dec 10;PP. doi: 10.1109/JBHI.2024.3514669. Online ahead of print.

ABSTRACT

Inertial measurement units (IMUs) have become attractive for monitoring joint kinematics due to their portability and versatility. However, their limited accuracy, inability to analyze data in real-time, and complex data fusion algorithms requiring precise sensor-to-segment calibrations hinder their clinical and daily use. This paper introduces KEEN (KinEmatics Estimation Network), an innovative framework that exploits lightweight artificial neural networks (ANNs) to provide real-time predictions of multi-plane ankle kinematics using a minimal number of IMUs, without calibration requirements. Five ANN algorithms were developed and evaluated using 42 inputs derived from four IMUs in both intra-subject and inter-subject tasks. Extensive experimental results yielded exciting findings: even a single IMU located at the heel can provide clinically acceptable estimations of ankle kinematics, implying significant potential for cost and energy savings. Statistical analysis demonstrated the superiority of the developed Long Short-Term Memory (LSTM) network over the other models in intra-subject tasks, achieving impressive accuracy (RMSE: 1.88, MAE: 1.41, and r2 score: 0.930.01), indicating strong generalization within the same subject. In inter-subject tasks, the convolutional neural network (CNN) and the CNN-LSTM models showed comparable performance but statistically outperformed the other models in terms of estimation accuracy across various inputs. When using a single IMU, the CNN model achieved the lowest error (RMSE: 4.13, MAE: 3.33, and r2 score: 0.500.21), showcasing its effective generalization to new subjects. Furthermore, deploying the CNN into a microcontroller, with a sinlge IMU at the heel, resulted in promising real-time ankle kinematics estimations (RMSE: 3.34, MAE: 2.68 and r2 score: 0.630.07). Overall, this research highlights the potential of combining IMUs with ANNs as reliable and practical tools for early prevention and rehabilitation of ankle injuries.

PMID:40030476 | DOI:10.1109/JBHI.2024.3514669

Microsurgery. 2025 Mar;45(3):e70042. doi: 10.1002/micr.70042.

ABSTRACT

BACKGROUND: Massive weight loss (MWL) patients often experience breast sequelae characterized by difficult-to-treat emptying and ptosis due to altered skin quality. Silicone prosthesis use is associated with a high rate of ptosis recurrence. The use of DIEP flap allows simultaneous treatment of breast and abdominal deformities. This study aims to present our experience using the DIEP-free flap as an autologous breast prosthesis for volumetric breast augmentation in the postbariatric population.

METHODS: This study involved all postbariatric patients who underwent breast reshaping using a double DIEP-free flap. Patient demographics, operative details, and postoperative outcomes were evaluated. Patients filled out BREAST-Q and BODY-Q surveys both preoperatively and after 6 months to study the rate of satisfaction.

RESULTS: Twenty patients underwent breast reshaping with double DIEP-free flap between September 2020 and October 2023. The average age was 30 years, with an average weight loss of 52.2 kg. Sleeve gastrectomy was the most common bariatric surgery procedure (75%). The average duration of surgeries was 461.38 min. The average length of stay was 6.5 days. Two flaps required surgical revision, with one flap loss. Two complications have been registered for the donor site, one liponecrosis with wound dehiscence and one abdominal bulging. Statistically significant improvements were observed in satisfaction with breast appearance and psychological, physical, and sexual well-being.

CONCLUSIONS: In the postbariatric population, the DIEP flap represents a safe and reproducible surgical technique for addressing breast deformities. Autologous volumetric augmentation offers harmonious and stable long-term outcomes without secondary sequelae at the donor site.

PMID:40026196 | DOI:10.1002/micr.70042

J Cutan Med Surg. 2025 Mar 3:12034754251322778. doi: 10.1177/12034754251322778. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the awareness of and attitudes toward various aspects of sun-exposure risks and protection methods among Canadians.

METHODS: An online survey conducted from September 28 to October 18, 2021, included 17,001 participants aged 18 years and above from 17 countries across 5 continents; the data presented are those of the Canadian population (n = 1,000). The survey focused on demographics, sun-exposure habits, comprehension of risks, and knowledge of photoprotection. The results were analyzed using descriptive statistics to identify prevalent trends and discrepancies in sun-protective behaviours among Canadians.

RESULTS: The majority of Canadian respondents (93%) acknowledged the health risks associated with sun exposure. While 81% of Canadians reported using some form of sun protection, only 10% systematically implemented all recommended protective measures, highlighting a gap in knowledge translation. Misconceptions regarding the safety of tanned skin and the effectiveness of sunscreens were widespread, particularly in younger demographics and in individuals with darker skin. Knowledge and preventive behaviours were markedly better among individuals who regularly consult dermatologists.

CONCLUSIONS: This study highlights general awareness of sun-protective behaviours but a lack of universal and comprehensive implementation among Canadians. Given the knowledge gaps in younger demographics and darker skin phototypes, targeted educational initiatives are essential to correct prevalent misconceptions about sun exposure and tanned skin. Dermatologists and other health care professionals can play a pivotal role in education and primary prevention strategies for skin cancer and other sun-related comorbidities.

PMID:40026168 | DOI:10.1177/12034754251322778

Prague Med Rep. 2025;126(1):9-16. doi: 10.14712/23362936.2025.2.

ABSTRACT

Iliac crest is common site for harvesting bone grafts. Morphometry of iliac crest is of vital importance in orthopedic surgery. Measurements were done on male (n=85) and female (n=85) hip bones. Length of iliac crest, thickness of iliac crest and ilium were measured. Thickness was measured at pre-defined points on crest and ilium 2 cm apart starting from anterior superior iliac spine (ASIS). Ilium was measured at a depth of 2.5 cm from crest. Statistical analysis was done. Iliac crests were longer in male bones. Ventral iliac crest was thickest at 6 cm from ASIS in both sexes. While iliac crest bore minimum thickness at 12 cm and 10 cm from ASIS in male and female bones respectively, however at 2.5 cm below iliac crest surface ilium was thickest at 4 cm from ASIS and at ASIS in male and female bones respectively. In case of male bones, dorsal part of iliac crest was thickest at 2.15 ± 1.29 cm from posterior superior iliac spine (PSIS) while in females it was at 1.78 ± 1.31 cm from PSIS. In dorsal part of ilium, it was observed at 2.31 ± 1.47 cm and 1.9 ± 1.79 cm from PSIS for male and female bones respectively. This study provided detailed variable morphometry and significant sexual dimorphism observed in iliac crest and ilium. Thickest safe zones in both sexes are a useful guide for harvesting appropriate bone grafts.

PMID:40026158 | DOI:10.14712/23362936.2025.2

Circ Cardiovasc Qual Outcomes. 2025 Mar 3:e011188. doi: 10.1161/CIRCOUTCOMES.124.011188. Online ahead of print.

ABSTRACT

BACKGROUND: Previous observational studies showed left atrial appendage occlusions with the WATCHMAN device reduced 1-year mortality, which conflicted with evidence generated from randomized controlled trials. We proposed to use the high-dimensional propensity score (hdPS) to assist in nonactive comparator selection (prevalent user of medication) and compared 1-year mortality between patients with atrial fibrillation who received the WATCHMAN device (percutaneous left atrial appendage occlusion device [pLAAO]) and direct oral anticoagulants in 2 matched cohorts based on (1) traditional propensity score (PS) and (2) integrating traditional PS with information learned from hdPS.

METHODS: Patients entered the cohort once diagnosed with atrial fibrillation in the 15% of Medicare fee-for-service claims database from 2011 to 2018. Patients could enter the study cohort upon receiving WATCHMAN or at an outpatient visit with an atrial fibrillation diagnosis, respectively. We used PS matching with a 1:3 ratio for patients in pLAAO and direct oral anticoagulant groups. In cohort 2, we implemented a multistep approach with information learned from hdPS. The Cox proportional hazards model was used to estimate hazard ratios of outcomes with 95% CIs.

RESULTS: In cohort 1, we identified 1159 and 3477 patients in the pLAAO and direct oral anticoagulant groups with a mean age of 78.1 versus 77.5 years, 44.9% versus 40.8% of women, and a 1-year mortality rate of 8.02 versus 8.97/100 person-years (hazard ratio, 0.87 [95% CI, 0.69-1.09]). With the support of hdPS, in cohort 2, we excluded patients with malignant cancer and added frailty score in the PS model. We identified 953 and 2859 patients in the pLAAO and direct oral anticoagulant groups with a mean age of 78.1 versus 77.9 years, 47.2% versus 46.1% of women, and a 1-year mortality rate of 7.45 and 7.69/100 person-years (hazard ratio, 0.95 [95% CI, 0.73-1.24]).

CONCLUSIONS: No association was found between pLAAO and 1-year mortality, which is consistent with existing evidence from randomized controlled trials. The hdPS approach provides an opportunity to improve nonactive comparator selection in traditional PS analysis.

PMID:40026152 | DOI:10.1161/CIRCOUTCOMES.124.011188