Federated Learning on Heterogeneous Data via Adaptive Self-Distillation

Federated Learning (FL) is a machine learning paradigm that enables clients to jointly train a global model by aggregating the locally trained models without sharing any local training data. In practice, there can often be substantial heterogeneity (e.g., class imbalance) across the local data distributions observed by each of these clients. Under such non-iid data distributions across clients, FL suffers from the 'client-drift' problem where every client converges to its own local optimum. This results in slower convergence and poor performance of the aggregated model. To address this limitation, we propose a novel regularization technique based on adaptive self-distillation (ASD) for training models on the client side. Our regularization scheme adaptively adjusts to the client's training data based on: (1) the closeness of the local model's predictions with that of the global model and (2) the client's label distribution. The proposed regularization can be easily integrated atop existing, state-of-the-art FL algorithms leading to a further boost in the performance of these off-the-shelf methods. We demonstrate the efficacy of our proposed FL approach through extensive experiments on multiple real-world benchmarks (including datasets with common corruptions and perturbations) and show substantial gains in performance over the state-of-the-art methods

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic

Alcohol use and burden for 195 countries and territories, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016

Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2.2% (95% uncertainty interval [UI] 1.5-3.0) of age-standardised female deaths and 6.8% (5.8-8.0) of age-standardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3.8% (95% UI 3.2-4-3) of female deaths and 12.2% (10.8-13-6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2.3% (95% UI 2.0-2.6) and male attributable DALYs were 8.9% (7.8-9.9). The three leading causes of attributable deaths in this age group were tuberculosis (1.4% [95% UI 1. 0-1. 7] of total deaths), road injuries (1.2% [0.7-1.9]), and self-harm (1.1% [0.6-1.5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27.1% (95% UI 21.2-33.3) of total alcohol-attributable female deaths and 18.9% (15.3-22.6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0.0-0.8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption.Peer reviewe

Constrained Static/Dynamic Economic Emission Load Dispatch Using Elephant Herd Optimization

The rapid growth in greenhouse gases (GHGs), the lack of electricity production, and an ever-increasing demand for electrical energy requires an optimal reduction in coal-fired thermal generating units (CFTGU) with the aim of minimizing fuel costs and emissions. Previous approaches have been unable to deal with such problems due to the non-convexity of realistic scenarios and confined optimum convergence. Instead, meta-heuristic techniques have gained more attention in order to deal with such constrained static/dynamic economic emission load dispatch (ELD/DEELD) problems, due to their flexibility and derivative-free structures. Hence, in this work, the elephant herd optimization (EHO) technique is proposed in order to solve constrained non-convex static and dynamic ELD problems in the power system. The proposed EHO algorithm is a nature-inspired technique that utilizes a new separation method and elitism strategy in order to retain the diversity of the population and to ensure that the fittest individuals are retained in the next generation. The current approach can be implemented to minimize both the fuel and emission cost functions of the CFTGUs subject to power balance constraints, active power generation limits, and ramp rate limits in the system. Three test systems involving 6, 10, and 40 units were utilized to demonstrate the effectiveness and practical feasibility of the proposed algorithm. Numerical results indicate that the proposed EHO algorithm exhibits better performance in most of the test cases as compared to recent existing algorithms when applied to the static and dynamic ELD issue, demonstrating its superiority and practicability

Residency evaluation and adherence design study: Young ophthalmologists' perception of their residency programs II: Academics and Research dissertation

Purpose: To know the perception of young ophthalmologists about their dissertation and academics during residency training in order to improve the research output during present residency programs in India. Methods: A survey was conducted by Academic and Research Committee of the All India Ophthalmological Society, the world's second largest ophthalmic professional's organization, in 2014–2016 of young ophthalmologists (those who completed residency between 2005 and 2012) to gauge usefulness of dissertation or thesis during postgraduate residency. Results: There were 1005 respondents, of whom 531 fulfilled inclusion criteria. On a scale of 0–10, residents rated level of supervision of their dissertation as adequate (mean 5.9/10, standard deviation [SD] = 3.1, median = 6). The level of infrastructure available was for dissertation rated as 5.9/10 (median = 7, SD = 3.1), and 6.2/10 was the score that residents said about value added by the dissertation (median = 7). The dissertation was presented at local (33.5%), state (28.1%), national (15.4%), and international (4%) levels. Students, not supervisors, did most of the local and state level presentations. It was published in some forms at local 210 (39.5%), state (140, 26.4%), national (94, 17.7%), and international (39, 7.3%) levels. On a scale of 0–4, seminars (3/4) and case presentations were (3/4) rated higher than didactic lectures (2.2/4), journal clubs (2.2/4), and wet laboratory (1.1/4). Conclusion: Peer-reviewed publications from Indian residency training dissertations were few. Residents felt dissertation added value to their training, but there was a huge range among the responses. Journal clubs and wet laboratories were not graded high in academic programs, unlike seminars and case presentations

A retrospective observational study to evaluate the reliability of staging and risk stratification of adolescent and adult patients with Hodgkin's lymphoma registered at the lymphoma clinic of a tertiary cancer center in Western India

Background: The treatment for Hodgkin's lymphoma is based on risk stratification of the disease, which is determined by staging, clinical, and laboratory parameters. The current staging systems are highly prone to error due to overlapping components and inter-observer variability. Objectives: We aimed to assess the reliability of staging and risk stratification performed by the clinicians at our busy multidisciplinary clinic. Materials and Methods: We conducted a retrospective analysis of 115 patients with newly diagnosed Hodgkin's lymphoma at the Tata Memorial Hospital, Mumbai, India, from 2016-2018. Patients who underwent baseline staging and risk stratification in the multidisciplinary lymphoma clinic were included in the analysis. The multidisciplinary lymphoma clinic is a collaboration between medical oncologists, radiation oncologists, nurses, social workers, and patient navigators. The staging and risk stratification performed during the multidisciplinary clinic were compared with those of a team of independent experts from medical oncology, radiation oncology, and nuclear medicine based on standard references (guidelines established by the German Hodgkin Study Group and the Ann Arbor Staging). Results: Discordance rates of 11.3% (n = 13) in disease staging and 7.8% (n = 9) in risk stratification were observed between the multidisciplinary clinic and the independent expert team. In all the discordant cases, there was up-staging of patients by the multidisciplinary clinic; all nine patients in early favorable risk category were misclassified as early unfavorable. The discordance rates were not significant, with a kappa score of 0.841 for staging and 0.855 for risk stratification. Conclusion: Misclassification of patients with Hodgkin's lymphoma based on the staging, and risk stratification may lead to over- or under-treatment. There is a need for a simpler, objective, and technology-driven risk stratification process

Development of Predisposition,Injury,Response,Organ failure model for predicting acute kidney injury in acute on chronic liver failure.

Background and Aim There is limited data on predictors of acute kidney injury(AKI) in ACLF. We developed a PIRO model (Predisposition, Injury, Response, Organ failure) for predicting AKI in a multi-centric cohort of ACLF patients. Patients and Methods Data of 2360 patients from APASL-ACLF Research Consortium (AARC) was analysed. Multivariate logistic regression model (PIRO score) was developed from a derivation cohort (n=1363) which was validated in another prospective multicentric cohort of ACLF patients (n=997) Results Factors significant for P component were serum creatinine[(≥2mg/dl)OR 4.52, 95% CI (3.67-5.30)], bilirubin [(/dL,OR 1) versus (12-30 mg/dL,OR 1.45, 95% 1.1-2.63) versus (≥30 mg/dL,OR 2.6, 95% CI 1.3-5.2)], serum potassium [(/LOR-1)versus (3-4.9 mmol/L,OR 2.7, 95% CI 1.05-1.97) versus (≥5 mmol/L,OR 4.34, 95% CI 1.67-11.3)] and blood urea (OR 3.73, 95% CI 2.5-5.5); for I component nephrotoxic medications (OR-9.86, 95% CI 3.2-30.8); for R component,Systemic Inflammatory Response Syndrome,(OR-2.14, 95% CI 1.4-3.3); for O component, Circulatory failure (OR-3.5, 95% CI 2.2-5.5). The PIRO score predicted AKI with C-index of 0.95 and 0.96 in the derivation and validation cohort.The increasing PIRO score was also associated with mortality (p \u3c 0.001) in both the derivation and validation cohorts. Conclusions The PIRO model identifies and stratifies ACLF patients at risk of developing AKI. It reliably predicts mortality in these patients, underscoring the prognostic significance of AKI in patients with ACLF