Effect of male partners' involvement and support on reproductive, maternal and child health and well-being in East Africa: A scoping review.

Background And Aims: East African countries have high rates of maternal and child mortality and morbidity. Studies have shown that the involvement of male partners in reproductive health can benefit maternal and child health (MCH). This scoping review aims to provide an overview of the evidence across East Africa that describes male partner involvement and its effect on maternal, reproductive, and child well-being.

Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis.

The full acceptance of Deep Learning (DL) models in the clinical field is rather low with respect to the quantity of high-performing solutions reported in the literature. End users are particularly reluctant to rely on the opaque predictions of DL models. Uncertainty quantification methods have been proposed in the literature as a potential solution, to reduce the black-box effect of DL models and increase the interpretability and the acceptability of the result by the final user.

Barriers and opportunities for health service access among fathers: A review of empirical evidence.

Issue Addressed: Engagement with health supports benefits the whole family, yet few health services report successful engagement of fathers. Our aim was to describe available evidence on barriers and opportunities relevant to health system access for fathers.

Methods: Scoping reviews were conducted seeking empirical evidence from (1) Australian studies and (2) international literature reviews.

Engaging culturally diverse fathers in maternal and family healthcare: Experiences and perspectives of healthcare professionals.

Issue Addressed: Australian maternal, family and child services increasingly espouse the value of being 'father-inclusive'. However, fathers report feeling excluded or marginalised during healthcare visits with their partners/infants, and experience barriers to engaging in perinatal healthcare at the community, individual and healthcare service level. These barriers may be amplified in men who are members of minority groups, such as those from culturally and linguistically diverse (CALD) backgrounds.

Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images.

Objectives: Determining the volume of brain lesions after trauma is challenging. Manual delineation is observer-dependent and time-consuming and cannot therefore be used in routine practice. The study aimed to evaluate the feasibility of an automated atlas-based quantification procedure (AQP) based on the detection of abnormal mean diffusivity (MD) values computed from diffusion-weighted MR images.

Subtle anomaly detection: Application to brain MRI analysis of de novo Parkinsonian patients.

With the advent of recent deep learning techniques, computerized methods for automatic lesion segmentation have reached performances comparable to those of medical practitioners. However, little attention has been paid to the detection of subtle physiological changes caused by evolutive pathologies, such as neurodegenerative diseases. In this work, we leverage deep learning models to detect anomalies in brain diffusion tensor imaging (DTI) parameter maps of recently diagnosed and untreated (de novo) patients with Parkinson's disease (PD).

Evolving partnerships: engagement methods in an established health services research team.

Background: The Translating Research in Elder Care (TREC) program is a partnered health services research team that aims to improve the quality of care and quality of life for residents and quality of worklife for staff in nursing homes. This team includes academic researchers, trainees, research staff, citizens (persons living with dementia and family/friend caregivers of persons living in nursing homes), and decision-makers (ministries of health, health authorities, operators of nursing homes). The TREC team has experience working with health system partners but wanted to undertake activities to enhance the collaboration between the academic researchers and citizen members.

The voices of lived experience: reflections from citizen team members in a long-term care research program.

Background: The Translating Research in Elder Care (TREC) program is a partnered health services research team that aims to improve the quality of care and quality of life for residents and quality of worklife for staff in nursing homes. The TREC team undertook several activities to enhance the collaboration between the academic researchers and us, the citizen members. Known as VOICES (Voice Of (potential) Incoming residents, Caregivers Educating uS) we aim to share our experience working with a large research team.

Fathers' involvement in perinatal healthcare in Australia: experiences and reflections of Ethiopian-Australian men and women.

Background: Family-centred maternity care models include the expectation that fathers prepare for and attend the birth. In Australia over 20% of the population is from a culturally and linguistically diverse background. Public policies espouse culturally competent healthcare.

Neurovascular multiparametric MRI defines epileptogenic and seizure propagation regions in experimental mesiotemporal lobe epilepsy.

Objective: Improving the identification of the epileptogenic zone and associated seizure-spreading regions represents a significant challenge. Innovative brain-imaging modalities tracking neurovascular dynamics during seizures may provide new disease biomarkers.

Methods: With use of a multi-parametric magnetic resonance imaging (MRI) analysis at 9.

Bayesian Inverse Regression for Vascular Magnetic Resonance Fingerprinting.

Standard parameter estimation from vascular magnetic resonance fingerprinting (MRF) data is based on matching the MRF signals to their best counterparts in a grid of coupled simulated signals and parameters, referred to as a dictionary. To reach a good accuracy, the matching requires an informative dictionary whose cost, in terms of design, storage and exploration, is rapidly prohibitive for even moderate numbers of parameters. In this work, we propose an alternative dictionary-based statistical learning (DB-SL) approach made of three steps: 1) a quasi-random sampling strategy to produce efficiently an informative dictionary, 2) an inverse statistical regression model to learn from the dictionary a correspondence between fingerprints and parameters, and 3) the use of this mapping to provide both parameter estimates and their confidence indices.

Male partner involvement in birth preparedness, complication readiness and obstetric emergencies in Sub-Saharan Africa: a scoping review.

Background: Maternal mortality remains a pressing concern across Sub-Sahara Africa. The 'Three Delays Model' suggests that maternal deaths are a consequence of delays in: seeking care, reaching medical care and receiving care. Birth Preparedness and Complication Readiness (BPCR) refers to a plan organised during pregnancy in preparation for a normal birth and in case of complications.

Unannounced Meal Detection for Artificial Pancreas Systems Using Extended Isolation Forest.

This study aims at developing an unannounced meal detection method for artificial pancreas, based on a recent extension of Isolation Forest. The proposed method makes use of features accounting for individual Continuous Glucose Monitoring (CGM) profiles and benefits from a two-threshold decision rule detection. The advantage of using Extended Isolation Forest (EIF) instead of the standard one is supported by experiments on data from virtual diabetic patients, showing good detection accuracy with acceptable detection delays.

Characterization of Daily Glycemic Variability in Subjects with Type 1 Diabetes Using a Mixture of Metrics.

Glycemic variability (GV) is an important component of glycemic control for patients with type 1 diabetes (T1D). The inadequacy of existing measurements lies in the fact that they view the variability from different aspects, so that no consensus has been reached among physicians as to which metrics to use in practice. Moreover, although GV, from 1 day to another, can show very different patterns, few metrics have been dedicated to daily evaluations.

Glycemic variability indices can be used to diagnose islet transplantation success in type 1 diabetic patients.

Aims: High glycemic variability (GV) is the major indication for islet transplantation (IT) in patients with type 1 diabetes (T1D). The actual criteria used to assess graft function do not consider GV improvement. Our study aimed to describe GV indices' evolution in T1D patients who benefited from IT during the TRIMECO trial and to evaluate if thresholds might be defined to diagnose IT success.

Making mental health a priority on college campuses: implementing large scale screening and follow-up in a high enrollment gateway course.

We sought to evaluate a universal mental health screening program for undergraduate students using graduate student clinicians and online interviewing tools. Participants included 455 undergraduate students. Data were collected from October 2017 through January 2018.

No Structural Differences Are Revealed by VBM in 'De Novo' Parkinsonian Patients.

The identification of brain morphological alterations in newly diagnosed PD patients (i.e. 'de novo') could potentially serve as a biomarker and accelerate diagnosis.

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure.

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner.

Fully Automatic Lesion Localization and Characterization: Application to Brain Tumors Using Multiparametric Quantitative MRI Data.

When analyzing brain tumors, two tasks are intrinsically linked, spatial localization, and physiological characterization of the lesioned tissues. Automated data-driven solutions exist, based on image segmentation techniques or physiological parameters analysis, but for each task separately, the other being performedmanually or with user tuning operations. In this paper, the availability of quantitative magnetic resonance (MR) parameters is combined with advancedmultivariate statistical tools to design a fully automated method that jointly performs both localization and characterization.

Male partner attendance at antenatal care and adherence to antenatal care guidelines: secondary analysis of 2011 Ethiopian demographic and health survey data.

Background: Complications during pregnancy, childbirth and the postpartum period present a significant and complex public health problem in low income countries such as Ethiopia. One strategy endorsed by the World Health Organisation (WHO) to improve maternal and child health outcomes is to encourage male partner involvement in pregnancy care. This research aimed to explore the relationships between 1) male attendance at antenatal care and 2) socio-economic and women's empowerment factors and adherence to focused antenatal care guidelines among women receiving care in Ethiopia.

EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis.

Data clustering has received a lot of attention and numerous methods, algorithms and software packages are available. Among these techniques, parametric finite-mixture models play a central role due to their interesting mathematical properties and to the existence of maximum-likelihood estimators based on expectation-maximization (EM). In this paper we propose a new mixture model that associates a weight with each observed point.

Raising awareness of research evidence among health professionals delivering dementia care: Are knowledge translation workshops useful?

Providing information about the latest research via educational sessions to health professionals caring for people with dementia may be insufficient to drive change. This project explored self-reported impacts on practice change of adding information about knowledge translation (KT) to a national dementia education program. Six national workshop days were held.

Self-image profile in children and adolescents with attention deficit/ hyperactivity disorder and the quality of life in their parents.

Objective: We explored the impact of clinical response to treatment for Attention Deficit/Hyperactivity Disorder (ADHD) in children and adolescents on the subsequent changes in their self-image profile, the quality of life of their parents, and its effect on socio-demographic variables.

Method: Conners Rating Scales for Parents (CPRS-R) and for Teachers (CTRS-R) completed at the time of entry to the service were repeated to measure clinical response to treatment; the Self-image Profiles for Children (SIP-C) and Adolescents (SIP-A), the World Health Organization Quality of Life (WHOQoL) questionnaire and postcode data were used to evaluate other domains.

Results: Data was collected for 53 boys (84%) and 10 girls (16%) with current mean age 11.