CYTOLOGICAL, ULTRASOUND AND BIOCHEMICAL CORRELATION IN HASHIMOTO’S THYROIDITIS, FARIDABAD, INDIA: A RETROSPECTIVE CROSS-SECTIONAL ANALYSIS.

Background Hashimoto’s thyroiditis, an autoimmune disorder that impairs thyroid hormone production via antibody-mediated destruction of thyroid cells, affects women more frequently and presents symptoms like weight gain and fatigue. This study investigates the correlation between cytomorphological, biochemical, and radiological findings in diagnosing this condition, utilizing Fine Needle Aspiration Cytology (FNAC) as a key diagnostic tool. Materials and methods A retrospective analysis of cytological, radiological, and biochemical parameters was done for 84 patients who underwent FNAC for Hashimoto’s Thyroiditis. The blood concentration of thyroid hormones was evaluated by the Thyroid Function Test (TFT). Thyroid ultrasound was done using a high-frequency linear ultrasound transducer. Results This study found Hashimoto's thyroiditis more common in females (95%) and primarily in those aged 20-40 years. Biochemical hypothyroidism (Thyroid function test) was observed in 50% of the selected patients, euthyroidism was observed in about 43% of the patients, and hyperthyroidism was observed in 7 % of the patients. Cytological findings showed mild, moderate, and dense lymphocytic infiltration in 32.15%, 41.66%, and 26.20% of patients across Grades I, II, and III, respectively. Moreover, 51% of the patients were affected with diffuse thyroiditis, 35% of the patients were affected with goiter, 8% of the patients were affected with thyroid nodules, and the remaining 6% of the patients were seen to be normal in the ultrasound findings.  Conclusion Hashimoto’s Thyroiditis is more prevalent in females, with elevated biochemical results linked to higher FNAC grades. Early detection of diffuse thyroiditis using ultrasound assists in predicting the disease before clinical signs appear. Integrating biochemical, cytology, and ultrasound findings can identify subclinical hypothyroidism.  Recommendation For early detection and precise staging of Hashimoto’s Thyroiditis, integrating cytomorphological, biochemical, and radiological diagnostics is advised. Future research should aim at refining treatment strategies based on these findings

Can ChatGPT Play the Role of a Teaching Assistant in an Introductory Programming Course?

The emergence of Large language models (LLMs) is expected to have a major impact on education. This paper explores the potential of using ChatGPT, an LLM, as a virtual Teaching Assistant (TA) in an Introductory Programming Course. We evaluate ChatGPT's capabilities by comparing its performance with that of human TAs in some of the important TA functions. The TA functions which we focus on include (1) grading student code submissions, and (2) providing feedback to undergraduate students in an introductory programming course. Firstly, we assess ChatGPT's proficiency in grading student code submissions using a given grading rubric and compare its performance with the grades assigned by human TAs. Secondly, we analyze the quality and relevance of the feedback provided by ChatGPT. This evaluation considers how well ChatGPT addresses mistakes and offers suggestions for improvement in student solutions from both code correctness and code quality perspectives. We conclude with a discussion on the implications of integrating ChatGPT into computing education for automated grading, personalized learning experiences, and instructional support.Comment: Under revie

Product Recommendation using Hadoop

Recommendation systems are used widely to provide personalized recommendations to users. Such systems are used by e-commerce and social networking websites to increase their business and user engagement. Day-to-day growth of customers and products pose a challenge for generating high quality recommendations. Moreover, they are even needed to perform many recommendations per second, for millions of customers and products. In such scenarios, implementing a recommendation algorithm sequentially has large performance issues. To address such issues, we propose a parallel algorithm to generate recommendations by using Hadoop map-reduce framework. In this implementation, we will focus on item-based collaborative filtering technique based on user's browsing history, which is a well-known technique to generate recommendations

Nationwide Trends in Inpatient Admissions of Pulmonary Hypertension in the United States from 2000 to 2013

Introduction: Pulmonary Hypertension (PH) is a disorder of the pulmonary vasculature with high mortality and bears a large economic burden on the healthcare system. We conducted a review of the largest inpatient database in the United States and analyzed the trends in hospitalizations due to PH from the turn of the century (2000) to 2013 to evaluate the rate of hospitalizations and determine the cost and mortality associated with PH. Material and methods: We analyzed the National Inpatient Sample Database (NIS) for all patients in which PH (Primary or Secondary) or cor pulmonale was the primary discharge diagnosis (ICD-9: 416.0, 416.8 and 416.9) from 2000 to 2013. The NIS is the largest all-payer inpatient database in the United States and contains data from approximately 8 million hospital stays each year. The statistical significance of the difference in the number of hospital discharges, lengths of stays and associated hospital costs over the study period was calculated. Results: In 2000, there were 12,066 hospital admissions with the principal discharge diagnosis of pulmonary hypertension, which increased to 13,605 admissions in 2013 (p \u3c 0.001). The mean length of stay for PH increased from 5.89 days to 6.67 days during this period (p = 0.04). During the same period, the hospital charges increase by 174.5% from US$24,973 in 2000 to US$ 68,545 in 2013 (Adjusted for inflation). The aggregate cost of hospital visits of a patient increased by 209.5% from US$301,324,218 in 2000 to US$ 932,554,725 in 2013. Conclusion: The number of inpatient discharges related to PH has increased even though the number of inpatient discharges with PAH has been reported to be lower in literature. The mean length of stay has also shown a mild increase. This increase is associated with a significant increase in the mean and aggregate cost. These inpatient costs associated with PH contribute significantly to the total healthcare burden. Further research on cost-effective evaluation and management of PH is required

Nationwide trends in inpatient admissions of pulmonary hypertension in the United States from 2000 to 2013

  INTRODUCTION: Pulmonary hypertension (PH) is a disorder of the pulmonary vasculature with high mortality and bears a large economic burden on the healthcare system. We conducted a review of the largest inpatient database in the United States and analyzed the trends in hospitalizations due to PH from the turn of the century (2000) to 2013 to evaluate the rate of hospitalizations and determine the cost and mortality associated with PH. MATERIAL AND METHODS: We analyzed the National Inpatient Sample Database (NIS) for all patients in which PH (Primary or Secondary) or cor pulmonale was the primary discharge diagnosis (ICD-9: 416.0, 416.8 and 416.9) from 2000 to 2013. The NIS is the largest all-payer inpatient database in the United States and contains data from approximately 8 million hospital stays each year. The statistical significance of the difference in the number of hospital discharges, lengths of stays and associated hospital costs over the study period was calculated. RESULTS: In 2000, there were 12,066 hospital admissions with the principal discharge diagnosis of pulmonary hypertension, which increased to 13,605 admissions in 2013 (p < 0.001). The mean length of stay for PH increased from 5.89 days to 6.67 days during this period (p = 0.04). During the same period, the hospital charges increase by 174.5% from US$24,973 in 2000 to US$ 68,545 in 2013 (Adjusted for inflation). The aggregate cost of hospital visits of a patient increased by 209.5% from US$301,324,218 in 2000 to US$ 932,554,725 in 2013. CONCLUSIONS: The number of inpatient discharges related to PH has increased even though the number of inpatient discharges with PAH has been reported to be lower in literature. The mean length of stay has also shown a mild increase. This increase is associated with a significant increase in the mean and aggregate cost. These inpatient costs associated with PH contribute significantly to the total healthcare burden. Further research on cost-effective evaluation and management of PH is required.

Company Similarity using Large Language Models

Identifying companies with similar profiles is a core task in finance with a wide range of applications in portfolio construction, asset pricing and risk attribution. When a rigorous definition of similarity is lacking, financial analysts usually resort to 'traditional' industry classifications such as Global Industry Classification System (GICS) which assign a unique category to each company at different levels of granularity. Due to their discrete nature, though, GICS classifications do not allow for ranking companies in terms of similarity. In this paper, we explore the ability of pre-trained and finetuned large language models (LLMs) to learn company embeddings based on the business descriptions reported in SEC filings. We show that we can reproduce GICS classifications using the embeddings as features. We also benchmark these embeddings on various machine learning and financial metrics and conclude that the companies that are similar according to the embeddings are also similar in terms of financial performance metrics including return correlation.Comment: 8 pages, 2 figures, 2 table

Quantifying Outlierness of Funds from their Categories using Supervised Similarity

Mutual fund categorization has become a standard tool for the investment management industry and is extensively used by allocators for portfolio construction and manager selection, as well as by fund managers for peer analysis and competitive positioning. As a result, a (unintended) miscategorization or lack of precision can significantly impact allocation decisions and investment fund managers. Here, we aim to quantify the effect of miscategorization of funds utilizing a machine learning based approach. We formulate the problem of miscategorization of funds as a distance-based outlier detection problem, where the outliers are the data-points that are far from the rest of the data-points in the given feature space. We implement and employ a Random Forest (RF) based method of distance metric learning, and compute the so-called class-wise outlier measures for each data-point to identify outliers in the data. We test our implementation on various publicly available data sets, and then apply it to mutual fund data. We show that there is a strong relationship between the outlier measures of the funds and their future returns and discuss the implications of our findings.Comment: 8 pages, 5 tables, 8 figure

Abdominal Skin Rash After TACE Due to Non-Target Embolization of Hepatic Falciform Artery

Transcatheter arterial chemoembolization (TACE) is a well-recognized procedure for management of hepatocellular carcinoma. We present a 54-year-old man who presented with a periumbilical maculopapular skin rash that developed after an otherwise uneventful TACE procedure. A retrospective review of imaging was consistent with non-target embolization of the hepatic falciform artery (HFA). He was treated with oral non-steroidal antiinflammatory medication for 3 weeks with improvement, but had slight skin induration and an excoriated papule at 6-month follow-up. Non-target embolization of HFA is very rare, but clinicians and interventionalists should be aware of this complication, especially in patients predisposed to enlargement of HFA