Google Trends: Opportunities and limitations in health and health policy research.

Web search engines have become pervasive in recent years, obtaining information easily on a variety of topics, from customer services and goods to practical information. Beyond these search interests, however, there is growing interest in obtaining health advice or information online. As a result, health and health policy researchers are starting to take note of potential data sources for surveillance and research, such as Google Trends™, a publicly available repository of information on real-time user search patterns. While research using Google Trends™ is growing, use of the dataset still remains limited. This paper offers an overview of the use of such data in a variety of contexts, while providing information on its strengths, limitations, and recommendations for further improvement

For investigate the role of ultrasound and platelets count as an important marker for the diagnosis and prognosis of dengue patients

Background: Dengue is although self limiting viral disease but if severe complications take place than it becomes lethal. Plasma leakage is main pathology which results in fluid deposits in various organs. This plasma leakage is related to platelet count. Most important thing in treating dengue patient is to know the complications at the earliest. And ultrasound is the most sensitive and easily approachable, cost effective investigation for detecting the complications.Methods: This cross-sectional observational pilot study was carried out in the department of radiodiagnosis, pandit bhagwat dayal Sharma institute of medical sciences, Rohtak. One hundred and two patients with serologically confirmed dengue fever were included in this study. Ultrasound examinations were carried out by ultrasound machine with 5-13 MHZ probe by radiologists. Abdomen and thorax scanning were done thoroughly. Important findings like Gall bladder thickening hepatomegaly, splenomegaly, free fluid which are pathological markers for dengue were specially seen. Then these findings are relate to the age group and platelet count.Results: By applying chi square test we found that there is statistically difference in number of patients in age group 16-30 yrs having gall bladder wall thickening, hepatomegaly, free fluid, splenomegaly and pleural effusion as compared to other age groups (p<0.05) an also in patients having less than 20,000 platelets, only gall bladder thickening, ascites and hepatomegaly were statistically more significant as compared to other groups having more number of platelets (p<0.05).Conclusions: So, ultrasound and platelet count are important markers for diagnosis and prognosis of dengue patients. Ultrasound and Platelets count are important markers for the diagnosis as well as prognosis of dengue patients

Imaging in phenytoin induced neurotoxicity: a case series

Phenytoin is a commonly used anti-epileptic drug for various types of seizure disorders except for absent seizures. Long term dose dependant neurological side effects of phenytoin therapy include cerebellar atrophy, cerebral atrophy and brain stem atrophy. Skull hyperostosis, gum hypertrophy and megaloblastic anemia are other known effects of Long term therapy. We present four cases depicting clinical and neuroimaging findings of Phenytoin induced Toxicity

POWER: Parallel Optimizations With Executable Rewriting

The hardware industry's rapid development of multicore and many core hardware has outpaced the software industry's transition from sequential to parallel programs. Most applications are still sequential, and many cores on parallel machines remain unused. We propose a tool that uses data-dependence profiling and binary rewriting to parallelize executables without access to source code. Our technique uses Bernstein's conditions to identify independent sets of basic blocks that can be executed in parallel, introducing a level of granularity between fine-grained instruction level and coarse grained task level parallelism. We analyze dynamically generated control and data dependence graphs to find independent sets of basic blocks which can be parallelized. We then propose to parallelize these candidates using binary rewriting techniques. Our technique aims to demonstrate the parallelism that remains in serial application by exposing concrete opportunities for parallelism

Predicting prognosis in large cohort of decompensated cirrhosis of liver (DCLD)- a machine learning (ML) approach

Background and aims: Onset of decompensation in cirrhosis is associated with poor outcome. The current clinico-biochemical tools have limited accuracy in predicting outcomes reliably. Identifying the predictors with precision model on the big data using artificial intelligence may improve predictability. We aimed to develop a machine learning (ML) based prognostic model for predicting 90 day survival in patients of cirrhosis presenting with decompensation. Method: We analysed electronic medical records retrospectively of hospitalised cirrhosis patients at the ILBS, with a complete 90-day follow-up. Clinical data, laboratory parameters and organ involvement were serially noted. AI-modelling was done after appropriate mining, feature engineering, splitted randomly into train and testsets (20:80). The class imbalance problem was handled by random over-sampling technique, to make balanced 50:50 ratios. After 10- fold cross validation, 3 repetitions and grid search for optimal hyper parameters, the XGB-CV model was chosen. AUC was the primary selection criteria and confusion matrix was used to compare AUCs between AI-models and existing indices; CTP and MELD-score. Results: Total of 6326 patients [mean age 48.2 ± 11.5 years, 84% male, Mean CTP 10.4 ± 2.2 and MELD Na-30.4 ± 11.9, alcohol 49.4%] were included. Ninety day mortality was 29.2%. Acute insult was identified in 80% cases; of which extra-hepatic 49%, hepatic 46% and unknown 5% cases respectively. The XGB-CV model had the best accuracy for prediction of 90 days event in the train set 0.90 (0.90–0.93), validation set 0.80 (0.79–0.81) and for overall dataset 0.80 (0.79– 0.81). The AUC of the XGB-CV model was better than CTP and MELD Na-score by 16% and 15% respectively. The prediction model considered 43 variables; 18 of which predicted the outcome, and 10 maximum contributors are shown in concordance classifier. The most contributors to poor outcome included, index presentation as HE, diagnosis of AD/ACLF/ESLD, PT-INR, serum creatinine, total bilirubin, acute insult etiology, prior decompensation, acute hepatic or extrahepatic insult, leukocyte count and present duration of illness. In the Decision Tree Model, the presence of HE, PT-INR and syndromic diagnosis of AD or ACLF/ESLD was able to stratify the patients into low (22%), intermediate (23–46%) and high risk (\u3e75%) of mortality at 90 days. Conclusion: The AI based current model developed using a large data base of CLD patients presenting with decompensation immensely adds to the current indices of liver disease severity and can stratify patients at admission. Simple ML algorithms using HE and INR besides syndromic presentation, could help treatment decisions and prognostication

A comparative study for assessment of post-operative sequelae following mandibular transalveolar molar extractions using ozone and dexamethasone

Objectives: Trans-alveolar extractions involve surgical removal of tooth that has its own postoperative sequelae, most commonly manifested as pain and swelling. This study aims to compare the efficacy of topical ozone and dexamethasone in management of post-operative sequelae after mandibular trans-alveolar molar extractions. Materials and Methods: Sixty patients requiring surgical removal of mandibular molars under local anesthesia were randomly allocated into two groups, each group consisting of 30 patients. Group 1 received Topical Ozonated Oil in the extraction socket post-operatively, while Group 2 was administered 8 mg dexamethasone injection post-operatively. The patients were checked for postoperative wound healing, pain and swelling on 1st, 3rd and 7th day. Results: The results showed comparatively similar results for the pain severity and swelling score at the 1st and 7th postoperative day in both the groups. A greater reduction of pain was noticed in Group 1 on 3rd postoperative day. Wound Healing was noted to be better in Group 1 at 3rd and 7th post-operative day. Conclusion: In conclusion, topical ozone therapy can be used as an effective alternative treatment modality, when compared to dexamethasone for better management of post-operative sequelae following mandibular trans-alveolar molar extractions