Vision Encoder-Decoder Models for AI Coaching

This research paper introduces an innovative AI coaching approach by integrating vision-encoder-decoder models. The feasibility of this method is demonstrated using a Vision Transformer as the encoder and GPT-2 as the decoder, achieving a seamless integration of visual input and textual interaction. Departing from conventional practices of employing distinct models for image recognition and text-based coaching, our integrated architecture directly processes input images, enabling natural question-and-answer dialogues with the AI coach. This unique strategy simplifies model architecture while enhancing the overall user experience in human-AI interactions. We showcase sample results to demonstrate the capability of the model. The results underscore the methodology's potential as a promising paradigm for creating efficient AI coach models in various domains involving visual inputs. Importantly, this potential holds true regardless of the particular visual encoder or text decoder chosen. Additionally, we conducted experiments with different sizes of GPT-2 to assess the impact on AI coach performance, providing valuable insights into the scalability and versatility of our proposed methodology.Comment: 6 pages, 2 figure

ALTERED ARTERIAL DOPPLER FLOW PATTERN AND PERINATAL OUTCOME IN INTRAUTERINE GROWTH RESTRICTION

ABSTRACTObjectives: Intrauterine growth restriction (IUGR) is one of the common conditions that interfere with the growth of the fetus accounting for 10-15%of pregnant woman. Literature explores a wide range of incidence of perinatal complication including mortality among IUGR pregnancies. Limiteddata available on these complications confined to coastal Karnataka and its association with abnormal arterial Doppler flow pattern. To study theperinatal complications associated with IUGR pregnancies and its prevalence in comparison to healthy controls of comparable gestational age.Methods: This cohort study screened 53 IUGR fetuses by an antenatal scan at gestational age of 27 weeks or more. The diagnosis of IUGR was madeaccording to established criteria from SOGC clinical practice guidelines August 2013. The data also included 48 appropriate for gestational age fetuseswith healthy mothers with the comparable gestational week. Experienced cardiac sonographer and gynecologist performed fetal echocardiography(ECHO) using Vivid 7, GE health-care system ECHO machine with the convex transducer of frequency 1.7-2.4 MHz. The study was conducted at southIndian tertiary care center.Results: This study included 53 IUGR cases and 48 non-IUGR controls. The mean age was 27±4.37 and 26.88±3.14 years in IUGR and non-IUGRgroups, respectively. Fetal Doppler study variables showed a significant decrease in peak aortic velocity and velocity time integral which was notevident on other valves, though mitral antegrade flow during atrial contraction was found to be lower among IUGR group. In two-dimensional chamberquantification of IUGR group revealed significant increase in pulmonary artery dimension, right ventricular (RV) dimension and RV thickness than thecontrol group (p<0.05). The anthropometric parameters such as weight and length; abdomen circumference was significantly lower in IUGR group,whereas head circumference found to be more in IUGR group (p<0.001). The gestational weeks at delivery was significantly different among twogroups with IUGR group depicting the early delivery group. p<0.001(35.58±2.92 and 38.5±0.96 in IUGR and non-IUGR groups, respectively). IUGRgroup also had prolonged neonatal intensive care unit stay when compared to controls (p<0.001).Conclusions: IUGR carries profound course in altered Doppler indices and cardiac function which explore its prediction on mortality and adverseperinatal outcome. This study showed significant perinatal mortality accounting for 5.6% among IUGR cases when compared to normal. Althoughtissue Doppler indices show normal variants, IUGR possesses significant adverse perinatal outcome, however with lesser incidence compared tosevere form of IUGR subsets who show altered tissue annular velocities.Keywords: Intrauterine growth restriction, Echocardiography, Doppler, Perinatal

Lipid Profile Parameters and Coronary Artery Disease in Young Patients Undergoing Diagnostic Angiography

Introduction: It is vital to understand the association between lipid profile and the severity of coronary artery disease (CAD) in young patients with suspected CAD. The clinical presentation, lipid profile and severity of CAD may differ in patients who develop CAD at young age and those at older age. Friesinger (FR) index is an important tool to assess the extent and severity of coronary artery lesions.Methods: This study was a single center retrospective study involving patients below 40 years who underwent diagnostic coronary angiography. Demographic variables, lipid profile and FR index were estimated. Patients were divided into four groups based on the FR index scores of 0, 1–4, 5–10 and 11-15, respectively.Results: A total of 158 patients (Mean ± SD of age; 35.65 ± 3.81 years) were included in the study. Among demographic variables, gender (P = 0.03) and body mass index (BMI) (P < 0.001) were found to be associated with FR index. In addition, total cholesterol (P < 0.001), low density cholesterol (LDL) cholesterol (P < 0.001), non-high density cholesterol (non-HDL) (P < 0.001) and ratio of triglycerides (TG) /non-HDL cholesterol (P = 0.004) showed significant differences between the FR groups. Logistic regression analysis showed that only diabetes (P = 0.02) and BMI (P = 0.004) were significant predictors of the extent and severity of coronary artery lesions in terms of FR index.Conclusions: A strong direct relationship was observed between total cholesterol, LDL and non HDL cholesterol while a negative correlation with the TG/non HDL ratio. Diabetes and BMI also play a very significant role

USE OF TISSUE DOPPLER IMAGING TO DETECT RIGHT VENTRICULAR MYOCARDIAL DYSFUNCTION IN PATIENTS WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE

Objective: To determine the utility of tissue Doppler imaging (TDI) in detecting early right ventricle (RV) myocardial dysfunction, given its prognostic implications in patients with chronic obstructive pulmonary disease (COPD).Methods:  A prospective case-control study was carried out involving 36 COPD patients in an acute exacerbated state as cases and 34 healthy subjects serving as controls. Each subject underwent a baseline echocardiography using various methods ranging from m-mode and 2-dimensional measures for analyzing RV geometry to strain and strain rate using Tissue Doppler Imaging to measure RV deformation. The cases underwent a subsequent echocardiogram 1month later once the respiratory symptoms subsided.Results: A significant difference was observed in RV tissue annular velocities ( E', A', S) between cases and the controls at baseline. However no significant increase was observed in tissue annular velocities among cases during remission states from baseline. Peak systolic strain in COPD group was significantly reduced in comparison to controls, but not significantly increased during remission when compared to baseline in cases. FEV1/VC did not bear any significant correlation with RV strain. Tei index had a negative linear correlation with peak systolic strain of RV, which was statistically significant.Conclusion: TDI parameters revealed that RV dysfunction remains unaltered even in remission state of COPD, despite pulmonary arterial pressure normalizing. In light of it bearing a negative prognosis in COPD, RV dysfunction merits assessment in COPD patients, both in acute exacerbations as well as in remission. Â

4-[4-Eth­oxy­carbonyl-5-(3,4-methyl­ene­dioxy­phen­yl)-3-oxocyclo­hex-1-en-1-yl]-3-phenyl­sydnone

In the title compound {systematic name: 4-[4-eth­oxy­carbonyl-5-(3,4-methyl­ene­dioxy­phen­yl)-3-oxocyclo­hex-1-en-1-yl]-3-phenyl-1,2,3-oxadiazol-3-ium-5-olate}, C24H20N2O7, the cyclo­hexene and dioxole rings adopt envelope conformations. The sydnone ring and the attached phenyl ring form a dihedral angle of 79.0 (1)°. In the mol­ecular structure, a C—H⋯O hydrogen bond generates an S(6) ring and a C—H⋯π inter­action involving the phenyl ring is observed. In the crystal structure, mol­ecules are linked into a ribbon-like structure along the a axis by C—H⋯O hydrogen bonds

Integrating artificial intelligence for knowledge management systems – synergy among people and technology: a systematic review of the evidence

This paper analyses Artificial Intelligence (AI) and Knowledge Management (KM) and focuses primarily on examining to what degree AI can help companies in their efforts to handle information and manage knowledge effectively. A search was carried out for relevant electronic bibliographic databases and reference lists of relevant review articles. Articles were screened and the eligibility was based on participants, procedures, comparisons, outcomes (PICO) model, and criteria for PRISMA (Preferred Reporting Items for Systematic Reviews). The results reveal that knowledge management and AI are interrelated fields as both are intensely connected to knowledge; the difference reflects in how – while AI offers machines the ability to learn, KM offers a platform to better understand knowledge. The research findings further point out that communication, trust, information systems, incentives or rewards, and the structure of an organization; are related to knowledge sharing in organizations. This systematic literature review is the first to throw light on KM practices & the knowledge cycle and how the integration of AI aids knowledge management systems, enterprise performance & distribution of knowledge within the organization. The outcomes offer a better understanding of efficient and effective knowledge resource management for organizational advantage. Future research is necessary on smart assistant systems thus providing social benefits that strengthen competitive advantage. This study indicates that organizations must take note of definite KM leadership traits and organizational arrangements to achieve stable performance through KM

Novel Hypertrophic Cardiomyopathy Diagnosis Index Using Deep Features and Local Directional Pattern Techniques

Hypertrophic cardiomyopathy (HCM) is a genetic disorder that exhibits a wide spectrum of clinical presentations, including sudden death. Early diagnosis and intervention may avert the latter. Left ventricular hypertrophy on heart imaging is an important diagnostic criterion for HCM, and the most common imaging modality is heart ultrasound (US). The US is operator-dependent, and its interpretation is subject to human error and variability. We proposed an automated computer-aided diagnostic tool to discriminate HCM from healthy subjects on US images. We used a local directional pattern and the ResNet-50 pretrained network to classify heart US images acquired from 62 known HCM patients and 101 healthy subjects. Deep features were ranked using Student's t-test, and the most significant feature (SigFea) was identified. An integrated index derived from the simulation was defined as 100.log(10 )(SigFea /root 2) in each subject, and a diagnostic threshold value was empirically calculated as the mean of the minimum and maximum integrated indices among HCM and healthy subjects, respectively. An integrated index above a threshold of 0.5 separated HCM from healthy subjects with 100% accuracy in our test dataset

Role of Four-Chamber Heart Ultrasound Images in Automatic Assessment of Fetal Heart: A Systematic Understanding

The fetal echocardiogram is useful for monitoring and diagnosing cardiovascular diseases in the fetus in utero. Importantly, it can be used for assessing prenatal congenital heart disease, for which timely intervention can improve the unborn child's outcomes. In this regard, artificial intelligence (AI) can be used for the automatic analysis of fetal heart ultrasound images. This study reviews nondeep and deep learning approaches for assessing the fetal heart using standard four-chamber ultrasound images. The state-of-the-art techniques in the field are described and discussed. The compendium demonstrates the capability of automatic assessment of the fetal heart using AI technology. This work can serve as a resource for research in the field

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Portal Annular Pancreas – A Case Report

Portal annular pancreas is one of the rarest congenital anomaly of the pancreas. This variation was noted in a formalin fixed male cadaver aged about 60yrs during the course of routine anatomy dissection in MVJ Medical college and research hospital.Here the pancreatic parenchyma not only enclosed the second part of duodenum but also had surrounded the portal vein (PV). Such a variation requires careful consideration by the surgeon and gastroenterologists while performing pancreatic resection and various other procedures pertaining to the pancreas and duodenum