Machine learning models to detect anxiety and depression through social media : a scoping review

Despite improvement in detection rates, the prevalence of mental health disorders such as anxiety and depression are on the rise especially since the outbreak of the COVID-19 pandemic. Symptoms of mental health disorders have been noted and observed on social media forums such Facebook. We explored machine learning models used to detect anxiety and depression through social media. Six bibliographic databases were searched for conducting the review following PRISMA-ScR protocol. We included 54 of 2219 retrieved studies. Users suffering from anxiety or depression were identified in the reviewed studies by screening their online presence and their sharing of diagnosis by patterns in their language and online activity. Majority of the studies (70%, 38/54) were conducted at the peak of the COVID-19 pandemic (2019–2020). The studies made use of social media data from a variety of different platforms to develop predictive models for the detection of depression or anxiety. These included Twitter, Facebook, Instagram, Reddit, Sina Weibo, and a combination of different social sites posts. We report the most common Machine Learning models identified. Identification of those suffering from anxiety and depression disorders may be achieved using prediction models to detect user's language on social media and has the potential to complimenting traditional screening. Such analysis could also provide insights into the mental health of the public especially so when access to health professionals can be restricted due to lockdowns and temporary closure of services such as we saw during the peak of the COVID-19 pandemic

Using Large Language Models to Automate Category and Trend Analysis of Scientific Articles: An Application in Ophthalmology

Purpose: In this paper, we present an automated method for article classification, leveraging the power of Large Language Models (LLM). The primary focus is on the field of ophthalmology, but the model is extendable to other fields. Methods: We have developed a model based on Natural Language Processing (NLP) techniques, including advanced LLMs, to process and analyze the textual content of scientific papers. Specifically, we have employed zero-shot learning (ZSL) LLM models and compared against Bidirectional and Auto-Regressive Transformers (BART) and its variants, and Bidirectional Encoder Representations from Transformers (BERT), and its variant such as distilBERT, SciBERT, PubmedBERT, BioBERT. Results: The classification results demonstrate the effectiveness of LLMs in categorizing large number of ophthalmology papers without human intervention. Results: To evalute the LLMs, we compiled a dataset (RenD) of 1000 ocular disease-related articles, which were expertly annotated by a panel of six specialists into 15 distinct categories. The model achieved mean accuracy of 0.86 and mean F1 of 0.85 based on the RenD dataset. Conclusion: The proposed framework achieves notable improvements in both accuracy and efficiency. Its application in the domain of ophthalmology showcases its potential for knowledge organization and retrieval in other domains too. We performed trend analysis that enables the researchers and clinicians to easily categorize and retrieve relevant papers, saving time and effort in literature review and information gathering as well as identification of emerging scientific trends within different disciplines. Moreover, the extendibility of the model to other scientific fields broadens its impact in facilitating research and trend analysis across diverse disciplines

Prevalence of stunting among under-five children in refugee and internally displaced communities: a systematic review and meta-analysis

BackgroundA pooled estimate of stunting prevalence in refugee and internally displaced under-five children can help quantify the problem and focus on the nutritional needs of these marginalized groups. We aimed to assess the pooled prevalence of stunting in refugees and internally displaced under-five children from different parts of the globe.MethodsIn this systematic review and meta-analysis, seven databases (Cochrane, EBSCOHost, EMBASE, ProQuest, PubMed, Scopus, and Web of Science) along with “preprint servers” were searched systematically from the earliest available date to 14 February 2023. Refugee and internally displaced (IDP) under-five children were included, and study quality was assessed using “National Heart, Lung, and Blood Institute (NHLBI)” tools.ResultsA total of 776 abstracts (PubMed = 208, Scopus = 192, Cochrane = 1, Web of Science = 27, Embase = 8, EBSCOHost = 123, ProQuest = 5, Google Scholar = 209, and Preprints = 3) were retrieved, duplicates removed, and screened, among which 30 studies were found eligible for qualitative and quantitative synthesis. The pooled prevalence of stunting was 26% [95% confidence interval (CI): 21–31]. Heterogeneity was high (I2 = 99%, p < 0.01). A subgroup analysis of the type of study subjects revealed a pooled stunting prevalence of 37% (95% CI: 23–53) in internally displaced populations and 22% (95% CI: 18–28) among refugee children. Based on geographical distribution, the stunting was 32% (95% CI: 24–40) in the African region, 34% (95% CI: 24–46) in the South-East Asian region, and 14% (95% CI: 11–19) in Eastern Mediterranean region.ConclusionThe stunting rate is more in the internally displaced population than the refugee population and more in the South-East Asian and African regions. Our recommendation is to conduct further research to evaluate the determinants of undernutrition among under-five children of refugees and internally displaced populations from different regions so that international organizations and responsible stakeholders of that region can take effective remedial actions.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=387156, PROSPERO [CRD42023387156]

Ocular Vascular Events following COVID-19 Vaccines: A Systematic Review

The main aim of this study is to investigate the current evidence regarding the association between COVID-19 vaccination and ocular vascular events. The protocol is registered on PROSPERO (CRD42022358133). On 18 August 2022, an electronic search was conducted through five databases. All original articles reporting individuals who were vaccinated with COVID-19 vaccines and developed ophthalmic vascular events were included. The methodological quality of the included studies was assessed using the NIH tool. A total of 49 studies with 130 ocular vascular cases were included. Venous occlusive events were the most common events (54.3%), which mostly occurred following the first dose (46.2%) and within the first five days following vaccination (46.2%). Vascular events occurred more with the Pfizer and AstraZeneca vaccines (81.6%), and mostly presented unilaterally (73.8%). The most frequently reported treatment was intravitreal anti-VEGF (n = 39, 30.4%). The majority of patients (90.1%) demonstrated either improvement (p = 0.321) or persistence (p = 0.414) in the final BCVA. Ophthalmic vascular events are serious vision-threatening side effects that have been associated with COVID-19 vaccination. Clinicians should be aware of the possible association between COVID-19 vaccines and ocular vascular events to provide early diagnosis and treatment

Rare congenital Dyserythropoietic anemia of childhood: A case report

Abstract Congenital dyserythropoietic anemias (CDA) is a heterogeneous class of anemia of varying degrees of ineffective erythropoiesis and secondary hemochromatosis. We reported a case of CDA and showed our approach to reaching a diagnosis, highlighting the importance of the typical morphological appearance of bone marrow erythroblasts to reach the diagnosis

Spontaneous idiopathic intratesticular hemorrhage as a differential diagnosis for acute scrotal pain

Abstract Background Spontaneous idiopathic testicular hemorrhage is an extremely rare entity with few published reports in the literature. Case presentation We report a case of a 15-year-old boy who had been experiencing intense, left scrotal pain for the previous twelve hours. No previous history of trauma or bleeding disorders. The left testis was enlarged and tender. Left orchiectomy was performed. The entire testis was dusty and dark grossly. Microscopic sections show diffuse intratesticular bleeding with intact seminiferous tubules and spermatogenesis. Conclusions Spontaneous idiopathic testicular hemorrhage should be considered when evaluating patients with acute scrotal pain. Clinical and ultrasonographic findings and histopathologic evaluation are mandatory to diagnose it

Ischemic stroke in the setting of supratherapeutic International Normalized Ratio following coronavirus disease 2019 infection: a case report

Abstract Background SARS-CoV-19 infection is associated with an increased risk of thrombotic events. We present a case of acute middle cerebral artery ischemic stroke in a patient with SARS-CoV-19 infection despite being on warfarin with supratherapeutic INR (International Normalized Ratio). Case presentation A 68-year-old Caucasian female with multiple comorbidities was admitted to the hospital with symptoms of upper respiratory tract infection. A rapid antigen test confirmed the diagnosis of COVID-19 pneumonia, and intravenous remdesivir was initiated. On the fifth day of admission, the patient experienced sudden onset confusion, slurred speech, left-sided hemiplegia, right-sided eye deviation, and left-sided facial droop. Imaging studies revealed an occlusion of the distal anterior M2 segment of the right middle cerebral artery, and an MRI of the brain confirmed an acute right MCA infarction. Notably, the patient was receiving warfarin therapy with a supratherapeutic INR of 3.2. Conclusions This case report highlights the potential for thromboembolic events, including stroke, in patients with COVID-19 infection, even when receiving therapeutic anticoagulation therapy. Healthcare providers should be vigilant for signs of thrombosis in COVID-19 patients, particularly those with pre-existing risk factors. Further research is necessary to understand the pathophysiology and optimal management of thrombotic complications in COVID-19 patients

The Characteristics of COVID-19 Vaccine-Associated Uveitis: A Summative Systematic Review

Numerous complications following COVID-19 vaccination has been reported in the literature, with an increasing body of evidence reporting vaccination-associated uveitis (VAU). In this systematic review, we searched six electronic databases for articles reporting the occurrence of VAU following COVID-19 vaccination. Data were synthesized with emphasis on patients’ characteristics [age, gender], vaccination characteristics [type, dose], and outcome findings [type, nature, laterality, course, location, onset, underlying cause, and associated findings]. Data are presented as numbers (percentages) for categorical data and as mean (standard deviation) for continuous data. Sixty-five studies were finally included [43 case reports, 16 case series, four cohort, one cross-sectional, and one registry-based study]. VAU occurred in 1526 cases, most commonly in females (68.93%) and middle-aged individuals (41–50 years: 19.71%), following the first dose (49.35%) of vaccination, especially in those who received Pfizer (77.90%). VAU occurred acutely (71.77%) as an inflammatory reaction (88.29%) in unilateral eyes (77.69%), particularly in the anterior portion of the uvea (54.13%). Importantly, most cases had a new onset (69.92%) while only a limited portion of cases had a reactivation of previous uveitis condition. In conclusion, although rare, uveitis following COVID-19 vaccination should be considered in new-onset and recurrent cases presenting with either acute or chronic events

Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review

BackgroundArtificial intelligence (AI)–driven serious games have been used in health care to offer a customizable and immersive experience. Summarizing the features of the current AI-driven serious games is very important to explore how they have been developed and used and their current state to plan on how to leverage them in the current and future health care needs. ObjectiveThis study aimed to explore the features of AI-driven serious games in health care as reported by previous research. MethodsWe conducted a scoping review to achieve the abovementioned objective. The most popular databases in the information technology and health fields (ie, MEDLINE, PsycInfo, Embase, CINAHL, IEEE Xplore, ACM Digital Library, and Google Scholar) were searched using keywords related to serious games and AI. Two reviewers independently performed the study selection process. Three reviewers independently extracted data from the included studies. A narrative approach was used for data synthesis. ResultsThe search process returned 1470 records. Of these 1470 records, 46 (31.29%) met all eligibility criteria. A total of 64 different serious games were found in the included studies. Motor impairment was the most common health condition targeted by these serious games. Serious games were used for rehabilitation in most of the studies. The most common genres of serious games were role-playing games, puzzle games, and platform games. Unity was the most prominent game engine used to develop serious games. PCs were the most common platform used to play serious games. The most common algorithm used in the included studies was support vector machine. The most common purposes of AI were the detection of disease and the evaluation of user performance. The size of the data set ranged from 36 to 795,600. The most common validation techniques used in the included studies were k-fold cross-validation and training-test split validation. Accuracy was the most commonly used metric for evaluating the performance of AI models. ConclusionsThe last decade witnessed an increase in the development of AI-driven serious games for health care purposes, targeting various health conditions, and leveraging multiple AI algorithms; this rising trend is expected to continue for years to come. Although the evidence uncovered in this study shows promising applications of AI-driven serious games, larger and more rigorous, diverse, and robust studies may be needed to examine the efficacy and effectiveness of AI-driven serious games in different populations with different health conditions

Diagnostic and prognostic role of elafin in skin acute graft versus host disease: a systematic review

ABSTRACTBackground and objective: Graft versus host disease (GVHD) is the common complication seen after allogeneic hematopoietic stem cell transplantation (HSCT) and a pleomorphic syndrome that resembles autoimmune and other immunologic disorders, leading to profound immune dysregulation and organ dysfunction. The most common targets of GVHD are skin, gastrointestinal tract and liver. GVHD is classified as acute graft versus host disease (aGvHD) if it occurs within the first 100 days after HSCT and chronic graft versus host disease(cGVHD) if it occurs after day 100. The skin is most frequently and earliest affected by aGvHD, followed by the gastrointestinal tract and liver. An ideal biomarker would predict the onset and severity of clinical acute GVHD and help to direct management, and this is an area of active research regarding the use of biomarkers for diagnosis and prognosis of acute GVHD. Recently, elafin has been identified as a potential plasma biomarker for aGVHD.Method: We searched the databases PubMed, Cochrane library, and medRxiv for all studies investigating the Diagnostic or prognostic role of elafin in GVHD. We set the search strategy incorporating the search terms, ‘elafin’, ‘graft versus host’, and ‘GVHD’, and operated using the Boolean operators ‘AND’, and ‘OR’. Thus, retrieved articles were then exported on an Excel® sheet, and duplicates were removed. The systematic review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After selecting the study based on inclusion criteria, data on study characteristics and biomarker description was extracted on a pre-determined data extraction table on the Microsoft Excel version. The quality assessment of the included studies was determined using the QUIPS tool.Result: The search revealed 547 studies and 6 studies that met the eligibility criteria of this review have been included. The major finding of our study is the significant elevation of elafin in skin aGVHD.Conclusion: Elafin is a significant biomarker for diagnosis and prognosis of skin aGVHD and should be assessed within 2 weeks of the onset of the disease