Diagnosed Health Conditions Research Articles

Use of specialist health care among Norwegian-born children with one immigrant parent

Abstract Background An increasing number of children grow up with one immigrant and one native born parent. We know little about health in this group. Our aim was to compare the risk of receiving diagnoses of physical health conditions in specialist health care among Norwegian-born children with one immigrant parent compared to Norwegian background children. Methods Data from Medical Birth Registry of Norway were linked to data from the Norwegian Patient Registry (diagnoses in specialist health care), and Statistics Norway (parental country of origin, education, and household income). We estimated hazard ratios (HR) with Cox proportional hazard regressions, with Norwegian background children as reference category, adjusted for sex, birth year, parental education, and household income. Results Children with an immigrant parent had lower hazards than Norwegian background children of diagnoses of most types of infections, but higher hazards of some, including tuberculosis, and skin infections. They also had higher hazards than Norwegian background children of receiving diagnoses of obesity and other nutritional deficiencies, and skin diseases, but lower hazards for other conditions, including chronic lower respiratory disease, disease of the digestive system, and visual or hearing impairment. The hazards of diagnoses of any neurological condition, sleeping disorders and epilepsy were lower among children with an immigrant mother, but higher among those with an immigrant father. Differences between children with one immigrant parent and Norwegian background could not be explained by differences in parental education or household income. Conclusions Children of one immigrant parent do not overall use specialist health care for physical health issues more than other children. Key messages • Awareness of diagnoses given most frequently to children of one immigrant parent can help promote timely diagnoses and adequate use of services, which is important for prevention of later illness. • Barriers to health care use among children of immigrants should be further researched.

Debate: How much should nonspecialists be involved in mental health care for children and young people when resources are limited?

From the barber-surgeons of the Middle Ages to the digitally enabled clinical interventions of today, the role of nonspecialists in delivering accessible health care remains relevant and important. Their contribution in developing and supporting appropriate interventions and care pathways in the community can make a big difference for the overwhelming majority of children and young people with diagnosable mental health conditions who are not eligible for specialist treatment or do not seek help. Even if resources for specialist services were unlimited, there are independent benefits in involving nonspecialists in mental health care, albeit not without limitations and concerns. The natural shift over time in the boundaries of specialisms, the omnipresence and omnipotence of digital media in our lives and the vision of 'no wrong door' for service users, mean that it is not a question of whether, but of how, nonspecialists should be involved. We need to get past the point of considering them just as alternative providers of mental health interventions and services. Instead, they are best placed to protect children and young people's mental health through ubiquitous everyday actions, which counter the negative and maximise the positive elements in current practices, environments and interactions that influence families and communities.

The potential impact of AI innovations on US occupations.

An occupation is comprised of interconnected tasks, and it is these tasks, not occupations themselves, that are affected by Artificial Intelligence (AI). To evaluate how tasks may be impacted, previous approaches utilized manual annotations or coarse-grained matching. Leveraging recent advancements in machine learning, we replace coarse-grained matching with more precise deep learning approaches. Introducing the AI Impact measure, we employ Deep Learning Natural Language Processing to automatically identify AI patents that may impact various occupational tasks at scale. Our methodology relies on a comprehensive dataset of 17,879 task descriptions and quantifies AI's potential impact through analysis of 24,758 AI patents filed with the United States Patent and Trademark Office between 2015 and 2022. Our results reveal that some occupations will potentially be impacted, and that impact is intricately linked to specific skills. These include not only routine tasks (codified as a series of steps), as previously thought but also nonroutine ones (e.g. diagnosing health conditions, programming computers, and tracking flight routes). However, AI's impact on labor is limited by the fact that some of the occupations affected are augmented rather than replaced (e.g. neurologists, software engineers, air traffic controllers), and the sectors affected are experiencing labor shortages (e.g. IT, Healthcare, Transport).

Long COVID Is Not a Functional Neurologic Disorder.

Long COVID is a common sequela of SARS-CoV-2 infection. Data from numerous scientific studies indicate that long COVID involves a complex interaction between pathophysiological processes. Long COVID may involve the development of new diagnosable health conditions and exacerbation of pre-existing health conditions. However, despite this rapidly accumulating body of evidence regarding the pathobiology of long COVID, psychogenic and functional interpretations of the illness presentation continue to be endorsed by some healthcare professionals, creating confusion and inappropriate diagnostic and therapeutic pathways for people living with long COVID. The purpose of this perspective is to present a clinical and scientific rationale for why long COVID should not be considered as a functional neurologic disorder. It will begin by discussing the parallel historical development of pathobiological and psychosomatic/sociogenic diagnostic constructs arising from a common root in neurasthenia, which has resulted in the collective understandings of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and functional neurologic disorder (FND), respectively. We will also review the case definition criteria for FND and the distinguishing clinical and neuroimaging findings in FND vs. long COVID. We conclude that considering long COVID as FND is inappropriate based on differentiating pathophysiologic mechanisms and distinguishing clinical findings.

Cross-Recurrence Quantification Of Cardiovascular Signals In Newborns Is A Sensitive Marker Of Health Status

Background — Analysis of the state of complex biological systems requires the use of sensitive methods for diagnosing interactions using experimental time series. Objective — To evaluate the possibility of using the technique of cross-recurrence quantification (CRQ) in studying the health status of newborns using low-frequency components of RR-interval signals and photoplethysmograms, reflecting the dynamics of the circuits in autonomic regulation of blood circulation. Methods — The study included two groups of neonates: 10 full-term newborns and 10 preterm neonates. We carried out simultaneous recording of electrocardiographic and photoplethysmographic signals. CRQ analysis was employed as the primary tool. Results — We established that some indices of CRQ analysis, characterizing the degree of interaction of the studied circuits, act as sensitive markers. They make it possible to distinguish the dynamics of the studied contours between healthy newborns and preterm neonates. Conclusion — The results of our study confirmed that CRQ is a promising tool in creating methods for diagnosing health conditions, including in newborns.

Beyond physical pain: A large-scale cohort study on endometriosis trends and mental health correlates

BackgroundThis study investigates the increased prevalence of endometriosis in Israel and its association with psychiatric comorbidities, focusing on the timing of psychiatric diagnoses in relation to endometriosis diagnosis. MethodsEmploying a retrospective cohort analysis, we reviewed data from 1,291,963 patients in a large scale medical database, identifying 24,259 cases (1.88%) of endometriosis. The analysis included demographic details, ICD-10 diagnoses of endometriosis and mental health conditions, and medication use patterns. ResultsA marked rise in endometriosis diagnosis was observed, particularly among women born between 1973 and 1978. Those with endometriosis were more likely to have psychiatric disorders—such as mood disorders, anxiety, PTSD, and eating disorders—than the control group, with the majority of psychiatric diagnoses occurring prior to endometriosis detection, except for PTSD. The study also highlighted significant sociocultural and socioeconomic disparities in endometriosis diagnosis, suggesting barriers to healthcare access and the influence of cultural factors. Limitations include potential biases from the retrospective design and the specific context of Israel's healthcare system, which may limit generalizability. ConclusionsThe significant rise in endometriosis and its strong association with psychiatric comorbidities, predominantly preceding the diagnosis of endometriosis, underscores the necessity for integrated care approaches. The disparities in diagnosis rates call for culturally sensitive healthcare practices and early psychiatric interventions.

The embodiment of exclusionary displacement pressure: Intersections of housing insecurity and mental health in a Hispanic/Latinx immigrant neighborhood

Gentrification, growing income inequality, urban development, and the affordable housing crisis necessitate understanding the impact of the concern of displacement on health — prior to or even in the absence of a displacement event. In this paper, I use the term “exclusionary displacement pressure” to unify the literature on exclusionary displacement and displacement pressure, highlighting the disproportionate and inequitable impacts of displacement pressure among communities of color. Through following 35 residents over 2.5-years (2019–2022) in one predominantly low-income Hispanic/Latinx immigrant neighborhood in Denver, Colorado, I examine how exclusionary displacement pressure shapes their health and wellbeing over time. Through paying attention to how participants' lived experience is shaped by structural vulnerability (e.g. lack of documentation status, inadequate work, limited access to safety net systems), I identify how exclusionary displacement pressure is constantly internalized and responded to as a unique embodied health experience, wearing on individuals over time and reproducing population health inequities. The framework of embodied health experiences captures the wide range of health-related impacts, from diagnosable health conditions to idioms of distress, using participant's own language of suffering to express how they were feeling, battling, and enduring the pressure. Theorizing on structural vulnerability within specific subpopulations with intersecting identities, such as low-income immigrant Hispanic/Latinx communities, provides a bottom-up refinement to existing theories of embodied health. Understanding the place-health experiences of individuals in changing neighborhoods over time is also critically important to define time points at which context-specific supports and interventions are appropriate.

An Expanded Approach to the Ascertainment of Children and Youth With Special Health Care Needs.

To describe the prevalence, characteristics, and health-related outcomes of children with diagnosed health conditions and functional difficulties who do not meet criteria for having a special health care need based on the traditional scoring of the Children with Special Health Care Needs (CSHCN) Screener. Data come from the 2016 to 2021 National Survey of Children's Health (n = 225 443). Child characteristics and health-related outcomes were compared among 4 mutually exclusive groups defined by CSHCN Screener criteria and the presence of both conditions and difficulties. Among children who do not qualify as children and youth with special health care needs (CYSHCN) on the CSHCN Screener, 6.8% had ≥1 condition and ≥1 difficulty. These children were more likely than CYSHCN to be younger, female, Hispanic, uninsured, privately insured, living in a household with low educational attainment, have families with more children and a primary household language other than English. After adjustment, non-CYSHCN with ≥1 conditions and ≥1 difficulty were less likely than CYSHCN, but significantly more likely than other non-CYSHCN, to have ≥2 emergency department visits, have unmet health care needs, not meet flourishing criteria, live in families that experienced child health-related employment impacts and frustration accessing services. Including these children in the calculation of CYSHCN prevalence increases the national estimate from 19.1% to 24.6%. Approximately 4 million children have both a diagnosed health condition and functional difficulties but are not identified as CYSHCN. An expanded approach to identify CYSHCN may better align program and policy with population needs.

Exploring the co-occurrence of depression, anxiety and insomnia symptoms, diagnoses and treatments in primary care: observational study using UK primary care data.

Depression, anxiety and insomnia often co-occur. However, there is a lack of research regarding how they cluster and how this is related to medication used to treat them. To describe the frequencies and associations between depression, anxiety and insomnia, and treatment for these conditions in primary care. A retrospective cohort study using UK electronic primary care records. We included individuals aged between 18 and 99 years old with one or more records suggesting they had a diagnosis, symptom or drug treatment for anxiety, depression or insomnia between 2015 and 2017. We report the conditional probabilities of having different combinations of diagnoses, symptoms and treatments recorded. There were 1 325 960 records indicative of depression, anxiety or insomnia, for 739 834 individuals. Depression was the most common condition (n = 106 117 records), and SSRIs were the most commonly prescribed medication (n = 347 751 records). Overall, individuals with a record of anxiety were most likely to have co-occurring symptoms and diagnoses of other mental health conditions. For example, of the individuals with a record of generalised anxiety disorder (GAD), 24% also had a diagnosis of depression. In contrast, only 0.6% of those who had a diagnosis of depression had a diagnosis or symptom of GAD. Prescribing of more than one psychotropic medication within the same year was common. For example, of those who were prescribed an SNRI (serotonin-norepinephrine reuptake inhibitor), 40% were also prescribed an SSRI (selective serotonin reuptake inhibitor). The conditional probabilities of co-occurring anxiety, depression and insomnia symptoms, diagnoses and treatments are high.

Nadifit, data-driven diagnosis: a clinical study for evaluating the significance of traditional Chinese medicine organ patterns through pulse diagnosis (nadi pariksha) for accurate pathology predictions

Background: Pulse diagnosis or nadipariksha, is a traditional diagnostic technique utilized in ayurveda and traditional Chinese medicine, analyzing various pulse characteristics such as force, patterns, rate, and rhythm to discern underlying health conditions. This method integrates TCM's five-element energy levels and Ayurveda's Tridosha levels to accurately identify the root cause of diseases, enabling practitioners to tailor treatments accordingly. In today's fast-paced world, the need for efficient health monitoring is imperative. However, finding expert practitioners proficient in pulse diagnosis is becoming increasingly challenging, necessitating the development of systems capable of providing personalized health insights based on accurate root-cause analysis. Methods: In this study, we compared predicted symptoms derived from objective TCM organ pattern analysis using the Nadifit pulse diagnosis system with subjective clinical assessments of patients' symptoms. TCM organ patterns were determined based on the combination of five elements and their Yin/Yang energy levels. Pulse signals were collected from 105 individuals and compared with clinical evaluations of patients' symptoms. Results: The analysis revealed a high level of agreement between the clinical assessment of symptoms and the predicted organ patterns, with a Kappa coefficient of 0.82. This suggests that objective pulse analysis effectively identifies root causes, aligning with subjective assessments. Conclusions: The findings of this study underscore the validity and reliability of objective pulse analysis in diagnosing health conditions. By demonstrating significant agreement with subjective clinical assessments, this method provides a promising avenue for enhancing diagnostic accuracy and facilitating personalized treatment strategies based on individual health profiles.

Now is the time to advance mental health, addiction reform

In the complex patchwork of American health care, the rise in mental health illness affects millions of lives. With over 50 million Americans grappling with diagnosable mental health conditions, the urgency to address it cannot be overstated. Shockingly, this equates to more than one in five Americans navigating the often‐challenging terrain of mental illness. Among these, young adults find themselves particularly vulnerable, bearing a disproportionate burden of these challenges. However, the statistics become even more sobering when considering minority populations — a staggering 36% of multiracial Americans face mental health hurdles, underscoring the critical need for equitable access to care across all demographics.

The long shadow of accumulating adverse childhood experiences on mental health in the United Arab Emirates: implications for policy and practice.

This study investigates the cumulative effects of adverse childhood experiences (ACEs) on adult depression, anxiety, and stress in Abu Dhabi, controlling for demographic factors, lifestyle, and known health and mental health diagnoses. Utilizing a cross-sectional design and self-report measures, the research aims to fill a critical gap in understanding the specific impacts of ACEs in the UAE. Based on a multi-site, cross-sectional community sample of 697 residents of Abu Dhabi. The findings reveal significant variances in current screening values for depression, anxiety, and stress attributable to ACEs after controlling for demographic factors, lifestyle risk factors, and adult diagnoses of health and mental health conditions. The results underline the lifelong impact of ACEs and reinforce the importance of early identification and intervention. In particular, the implications for policy and practice in understanding and mitigating ACEs long-term effects on mental health are considered.

Audiologists’ Perception of Hearing and Balance Health-care Resources and Services in Saudi Arabia

Background: Hearing loss and balance disorders are the most commonly diagnosed health conditions. The prevalence of these conditions is on the rise as the population ages and diagnostic and treatment technologies become more advanced. The health-care system still struggles to meet many nations’ needs due to insufficient resources and services. The objective of the study was to evaluate audiologists’ perceptions of hearing and balance health-care resources and services in Saudi Arabia’s public health system. Materials and Methods: A questionnaire survey was conducted through E-mail, social media, mobile phone, and face-to-face with audiologists across the Kingdom of Saudi Arabia, with the final sample consisting of 66 audiologists. Results: The majority (92.4%) of audiologists in Saudi Arabia indicated that the services are inadequate because their hospitals lack adequate hearing health-care resources to provide efficient audiology services to patients. Video head impulse test and automated auditory brain stem response were perceived as unavailable in most hospitals. In addition, audiologists reported that vestibular rehabilitation services, cochlear implants, and the number of clinics were limited. Conclusion: Great efforts should be made to develop audiovestibular services, which include enhancing practitioners’ vestibular knowledge by implementing more vestibular workshops; more vestibular clinics are needed to overcome the shortage of vestibular services; creating public awareness campaigns about vestibular and audiology; and hiring additional audiologists where needed within Saudi Arabia.

Recurrent otitis media and behaviour problems in middle childhood: A longitudinal cohort study.

To investigate the long-term effects of early-life recurrent otitis media (OM) and subsequent behavioural problems in children at the age of 10 years. Data from the Raine Study, a longitudinal pregnancy cohort, were used to categorise children into those with three or more episodes of OM (rOM group) and those without a history of recurrent OM in the first 3 years of life (reference group). The parent report Strengths and Difficulties Questionnaire was used to assess child behaviour at the age of 10 years. Parental questionnaires were used to report past and present diagnoses of various mental health and developmental conditions, including attention, anxiety, depression, learning, and speech-language problems. Multiple linear and logistic models were used to analyse the data and were adjusted for a fixed set of key confounding variables. The linear regression analysis revealed significant, independent associations between a history of recurrent OM and higher Strengths and Difficulties Questionnaire scores, including total, internalising, externalising, emotional, attention/hyperactivity and peer problems subscales. Logistic regression analyses revealed an independent increased likelihood for children in the rOM group to have a diagnosis of attention, anxiety, learning and speech-language problems. Children at 10 years of age with an early history of recurrent OM are more likely to exhibit attentional and behavioural problems when compared to children without a history of recurrent OM. These findings highlight the association between early-life recurrent OM and later behavioural problems that may require professional allied health-care interventions.

The Accuracy and Potential Racial and Ethnic Biases of GPT-4 in the Diagnosis and Triage of Health Conditions: Evaluation Study.

Whether GPT-4, the conversational artificial intelligence, can accurately diagnose and triage health conditions and whether it presents racial and ethnic biases in its decisions remain unclear. We aim to assess the accuracy of GPT-4 in the diagnosis and triage of health conditions and whether its performance varies by patient race and ethnicity. We compared the performance of GPT-4 and physicians, using 45 typical clinical vignettes, each with a correct diagnosis and triage level, in February and March 2023. For each of the 45 clinical vignettes, GPT-4 and 3 board-certified physicians provided the most likely primary diagnosis and triage level (emergency, nonemergency, or self-care). Independent reviewers evaluated the diagnoses as "correct" or "incorrect." Physician diagnosis was defined as the consensus of the 3 physicians. We evaluated whether the performance of GPT-4 varies by patient race and ethnicity, by adding the information on patient race and ethnicity to the clinical vignettes. The accuracy of diagnosis was comparable between GPT-4 and physicians (the percentage of correct diagnosis was 97.8% (44/45; 95% CI 88.2%-99.9%) for GPT-4 and 91.1% (41/45; 95% CI 78.8%-97.5%) for physicians; P=.38). GPT-4 provided appropriate reasoning for 97.8% (44/45) of the vignettes. The appropriateness of triage was comparable between GPT-4 and physicians (GPT-4: 30/45, 66.7%; 95% CI 51.0%-80.0%; physicians: 30/45, 66.7%; 95% CI 51.0%-80.0%; P=.99). The performance of GPT-4 in diagnosing health conditions did not vary among different races and ethnicities (Black, White, Asian, and Hispanic), with an accuracy of 100% (95% CI 78.2%-100%). P values, compared to the GPT-4 output without incorporating race and ethnicity information, were all .99. The accuracy of triage was not significantly different even if patients' race and ethnicity information was added. The accuracy of triage was 62.2% (95% CI 46.5%-76.2%; P=.50) for Black patients; 66.7% (95% CI 51.0%-80.0%; P=.99) for White patients; 66.7% (95% CI 51.0%-80.0%; P=.99) for Asian patients, and 62.2% (95% CI 46.5%-76.2%; P=.69) for Hispanic patients. P values were calculated by comparing the outputs with and without conditioning on race and ethnicity. GPT-4's ability to diagnose and triage typical clinical vignettes was comparable to that of board-certified physicians. The performance of GPT-4 did not vary by patient race and ethnicity. These findings should be informative for health systems looking to introduce conversational artificial intelligence to improve the efficiency of patient diagnosis and triage.

The shock of COVID‐19 and the shock of rapid vaccine development on the value of senior life settlement contracts

AbstractIn this paper, we develop a model that can capture how COVID‐19 and the subsequent rapid vaccine development against COVID‐19 impacts the value of pools of senior life settlements. The pandemic unexpectedly boosted the mortality rates of senior citizens who had prior diagnoses of certain health conditions. Our model accounts for the existence and concentration of these COVID‐19 comorbidities in portfolios of senior life settlements. It is the concentration of assets linked to the mortality rates of a group who is at elevated risk to COVID‐19 and who is also the primary beneficiaries of the COVID‐19 vaccine that we examine. We illustrate how the shock of the pandemic increases the value of senior life settlements and how the accelerated development and distribution of COVID‐19 vaccines moderated this increase. Our model is general enough to simulate the impact on other financial contracts that are linked to individual mortality rates. These would include life insurance contracts, annuities, and health insurance policies.

Associations between constructs related to social relationships and mental health conditions and symptoms: an umbrella review

BackgroundLoneliness and social isolation are increasingly recognised as prevalent among people with mental health problems, and as potential targets for interventions to improve quality of life and outcomes, as well as for preventive strategies. Understanding the relationship between quality and quantity of social relationships and a range of mental health conditions is a helpful step towards development of such interventions.PurposeOur aim was to give an overview of associations between constructs related to social relationships (including loneliness and social isolation) and diagnosed mental conditions and mental health symptoms, as reported in systematic reviews of observational studies.MethodsFor this umbrella review (systematic review of systematic reviews) we searched five databases (PsycINFO, MEDLINE, EMBASE, CINAHL, Web of Science) and relevant online resources (PROSPERO, Campbell Collaboration, Joanna Briggs Institute Evidence Synthesis Journal). We included systematic reviews of studies of associations between constructs related to social relationships and mental health diagnoses or psychiatric symptom severity, in clinical or general population samples. We also included reviews of general population studies investigating the relationship between loneliness and risk of onset of mental health problems.ResultsWe identified 53 relevant systematic reviews, including them in a narrative synthesis. We found evidence regarding associations between (i) loneliness, social isolation, social support, social network size and composition, and individual-level social capital and (ii) diagnoses of mental health conditions and severity of various mental health symptoms. Depression (including post-natal) and psychosis were most often reported on, with few systematic reviews on eating disorders or post-traumatic stress disorder (PTSD), and only four related to anxiety. Social support was the most commonly included social construct. Our findings were limited by low quality of reviews and their inclusion of mainly cross-sectional evidence.ConclusionGood quality evidence is needed on a wider range of social constructs, on conditions other than depression, and on longitudinal relationships between social constructs and mental health symptoms and conditions.

The met and unmet health needs for HIV, hypertension, and diabetes in rural KwaZulu-Natal, South Africa: analysis of a cross-sectional multimorbidity survey

The convergence of infectious diseases and non-communicable diseases in South Africa is challenging to health systems. In this analysis, we assessed the multimorbidity health needs of individuals and communities in rural KwaZulu-Natal and established a framework to quantify met and unmet health needs for individuals living with infectious and non-communicable diseases. We analysed data collected between May 25, 2018, and March 13, 2020, from participants of a large, community-based, cross-sectional multimorbidity survey (Vukuzazi) that offered community-based HIV, hypertension, and diabetes screening to all residents aged 15 years or older in a surveillance area in the uMkhanyakude district in KwaZulu-Natal, South Africa. Data from the Vukuzazi survey were linked with data from demographic and health surveillance surveys with a unique identifier common to both studies. Questionnaires were used to assess the diagnosed health conditions, treatment history, general health, and sociodemographic characteristics of an individual. For each condition (ie, HIV, hypertension, and diabetes), individuals were defined as having no health needs (absence of condition), met health needs (condition that is well controlled), or one or more unmet health needs (including diagnosis, engagement in care, or treatment optimisation). We analysed met and unmet health needs for individual and combined conditions and investigated their geospatial distribution. Of 18 041 participants who completed the survey (12 229 [67·8%] were female and 5812 [32·2%] were male), 9898 (54·9%) had at least one of the three chronic diseases measured. 4942 (49·9%) of these 9898 individuals had at least one unmet health need (1802 [18·2%] of 9898 needed treatment optimisation, 1282 [13·0%] needed engagement in care, and 1858 [18·8%] needed a diagnosis). Unmet health needs varied by disease; 1617 (93·1%) of 1737 people who screened positive for diabetes, 2681 (58·2%) of 4603 people who screened positive for hypertension, and 1321 (21·7%) of 6096 people who screened positive for HIV had unmet health needs. Geospatially, met health needs for HIV were widely distributed and unmet health needs for all three conditions had specific sites of concentration; all three conditions had an overlapping geographical pattern for the need for diagnosis. Although people living with HIV predominantly have a well controlled condition, there is a high burden of unmet health needs for people living with hypertension and diabetes. In South Africa, adapting current, widely available HIV care services to integrate non-communicable disease care is of high priority. Fogarty International Center and the National Institutes of Health, the Bill & Melinda Gates Foundation, the South African Department of Science and Innovation, the South African Medical Research Council, the South African Population Research Infrastructure Network, and the Wellcome Trust. For the isiZulu translation of the abstract see Supplementary Materials section.

Classification of Alzheimer's Progression Using fMRI Data.

In the last three decades, the development of functional magnetic resonance imaging (fMRI) has significantly contributed to the understanding of the brain, functional brain mapping, and resting-state brain networks. Given the recent successes of deep learning in various fields, we propose a 3D-CNN-LSTM classification model to diagnose health conditions with the following classes: condition normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and Alzheimer's disease (AD). The proposed method employs spatial and temporal feature extractors, wherein the former utilizes a U-Net architecture to extract spatial features, and the latter utilizes long short-term memory (LSTM) to extract temporal features. Prior to feature extraction, we performed four-step pre-processing to remove noise from the fMRI data. In the comparative experiments, we trained each of the three models by adjusting the time dimension. The network exhibited an average accuracy of 96.4% when using five-fold cross-validation. These results show that the proposed method has high potential for identifying the progression of Alzheimer's by analyzing 4D fMRI data.

Overcoming Communication Barriers to Facilitate Healthcare Access for People with Intellectual Disability

Communication barriers are one of the many reasons why People with Intellectual Disability (PWID) are prevented from accessing appropriate healthcare services. As a result, the health of this population is poorer than the general population in many countries around the world. Understanding the nature of the limitations faced by PWID in language learning and communication forms the basis of creatively developing strategies to overcome them. Building bridges of understanding between the clinician and the PWID increases the chances of accurate diagnoses of health conditions, effective treatment, and an overall improved quality of life for the patient.