336 research outputs found
Responsible ML Datasets
No full textIn this study, we discuss the importance of Responsible Machine Learning Datasets through the lens of fairness, privacy, and regulatory compliance and present a large audit of Computer Vision datasets. The audit is conducted through evaluation of the proposed responsible rubric. After surveying over 100 datasets, our detailed analysis of 60 distinct datasets highlights a universal susceptibility to fairness, privacy, and regulatory compliance issues.
Please cite the paper below.
Mittal, Surbhi, Kartik Thakral, Richa Singh, Mayank Vatsa, Tamar Glaser, Cristian Canton Ferrer, Tal Hassner. "On Responsible Machine Learning Datasets Emphasizing Fairness Privacy and Regulatory Norms with Examples in Biometrics and Healthcare." Nature Machine Intelligence (2024).
@article{mittal2024responsible,
title={On Responsible Machine Learning Datasets Emphasizing Fairness Privacy and Regulatory Norms with Examples in Biometrics and Healthcare},
author={Mittal, Surbhi, and Thakral, Kartik and Singh, Richa and Vatsa, Mayank and Glaser, Tamar and Ferrer, Cristian Canton and Hassner, Tal},
journal={Nature Machine Intelligence},
year={2024},
publisher={Nature Publishing Group UK London}
Responsible ML Datasets
No full textIn this study, we discuss the importance of Responsible Machine Learning Datasets through the lens of fairness, privacy, and regulatory compliance and present a large audit of Computer Vision datasets. The audit is conducted through evaluation of the proposed responsible rubric. After surveying over 100 datasets, our detailed analysis of 60 distinct datasets highlights a universal susceptibility to fairness, privacy, and regulatory compliance issues.
Please cite the paper below.
Mittal, Surbhi, Kartik Thakral, Richa Singh, Mayank Vatsa, Tamar Glaser, Cristian Canton Ferrer, Tal Hassner. "On Responsible Machine Learning Datasets Emphasizing Fairness Privacy and Regulatory Norms with Examples in Biometrics and Healthcare." Nature Machine Intelligence (2024).
@article{mittal2024responsible,
title={On Responsible Machine Learning Datasets Emphasizing Fairness Privacy and Regulatory Norms with Examples in Biometrics and Healthcare},
author={Mittal, Surbhi, and Thakral, Kartik and Singh, Richa and Vatsa, Mayank and Glaser, Tamar and Ferrer, Cristian Canton and Hassner, Tal},
journal={Nature Machine Intelligence},
year={2024},
publisher={Nature Publishing Group UK London}
Evaluation of the Effect of Elective Tracheostomy on Morbidity and Mortality following Oesophageal Surgery with Neck Anastomosis
No full textINTRODUCTION:
Oesophageal surgery involves a major surgical and physiological insult to the body with associated significant morbidity and mortality. Oesophageal surgery remains a demanding surgical procedure for surgeons who deal with benign and malignant disease of oesophagus. Significant advances in perioperative and postoperative care have occurred in the past decade. However mortality and morbidity rates associated with oesophagectomy worldwide remain high. Major contributors to the mortality
and morbidity are post operative pulmonary complications.
Pulmonary complications remain the most common complications that develop after oesophageal surgery. The incidence of pulmonary complications has been reported to vary from 17% to 45% in published literature. These account for up to 50% of the hospital deaths in patients undergoing oesophagectomy.
20% of patients who undergo oesophageal surgery require prolonged ventilatory support and undergo tracheostomy in the intensive care setting.
The role of early tracheostomy in critically ill patients has been extensively studied6. Recent literature has shown that an early tracheostomy in the intensive care setting, for patients requiring prolonged ventilation, reduces the duration of ventilation, duration of ICU stay and mortality. The timing of tracheostomy is still a matter of debate, but clearly there is a definite trend that the earlier tracheostomy is associated with better outcome in terms of morbidity and mortality.
Elective tracheostomy for patients undergoing major oesophageal surgery has not been studied so far, though some centers have been using the same in a few patients. This study aims at evaluating the effect of tracheostomy performed at the time of primary operation, in reducing pulmonary complications and improving outcomes after major oesophageal surgery.
AIMS AND OBJECTIVES:
To evaluate the effect of elective tracheostomy on morbidity
and mortality following oesophageal surgery with neck
anastomosis.
METHODOLOGY:
This study aimed at assessing the role of an elective tracheostomy in reduction of mortality and morbidity due to pulmonary complications in patients undergoing oesophageal surgery with neck anastomosis.
Design of Study:
Case control study with a prospective cohort of cases and a retrospective cohort of controls.
Selection Criteria:
Patients for the study were selected according to a set of inclusion and
exclusion criteria. They were as follows:
Inclusion criteria:
All patients undergoing oesophageal resection or bypass with a
cervical oesophageal anastomosis.i.e.
1. Substernal Colon Bypass for corrosive stricture oesophagus.
2. Mc Keowns oesophagectomy for benign or malignant oesophageal lesions.
3. Transhiatal oesophagectomy for oesophageal malignancies or benign oesophageal disease.
Exclusion criteria:
1. Patients undergoing laryngectomy.
2. Non consenting patients.
3. Patients found inoperable at surgery.
Duration of the Study:
The study extended from May 2005 to April 2007 (2 years) A retrospective cohort of controls was used. Controls were chosen using the same inclusion criteria over a period of May 2002 to April 2005 (3 years).
METHODOLOGY:
A review of all patients who confirmed to the inclusion criteria was done for the year 2004. The incidence of pulmonary complications among these patients was found to be 65%. 30% of these patients required prolonged ventilation and hence a tracheostomy. Aspiration pneumonia was the most common pulmonary complication (73 %) and was responsible for 50 % of the hospital deaths. Based on this data, the sample size was calculated to be 22.
Sample size = 4pq/d^2. Where, p = incidence of pulmonary complications (65%), q = 1-p (35%), d = expected difference in outcome (=20%).
After the detailed research plan was laid down, approval was obtained from the Department of Upper Gastrointestinal Surgery unit and the fluid research committee.
All patients fitting into the inclusion criteria were included in the study. Informed consent was taken prior to inclusion in the study. (Appendix 2).
All the include patients underwent an elective open surgical
tracheostomy at the end of surgery. They were then transferred to the surgical intensive care unit for further monitoring and ventilation if required.
No changes were made in the surgical intensive care protocols for monitoring these patients.
Number of cases enrolled:
There were a total of 56 patients enrolled for the study. These included 14 cases and 42 controls. This included patients undergoing transhiatal or transthoracic oesphagectomy and substernal colon pullthrough.
Patients who had undergone similar operations during the last 3 years were included in the control group.
CONCLUSION:
Prevention of pulmonary complications is the cornerstone to reduction of morbidity and mortality in oesophageal surgery.
This study reveals that if tracheostomy is done at the time of primary operation, there is a trend that the patients are weaned off the ventilator earlier and a shorter ICU stay. Also there is a trend that these patients are discharged earlier from hospital.
Although these differences did not reach stastical significance, there was a definite trend in the reduction of morbidity and mortality. This has clinical implications, especially with regard to ARDS and aspiration pneumonia. The small sample size and the absence of randomization in this study need to be kept in mind.
It has also been shown that a tracheostomy by itself is associated with minimal morbidity and is tolerated well by the patient.
With the above findings in mind, there is a strong case for a prospective randomized case control trial for evaluating elective tracheostomy as a strategy to reduce morbidity and mortality in patients undergoing oesophageal surgery
Approximation of Signals (Functions) by Trigonometric Polynomials in Lp-Norm
No full textMittal and Rhoades (1999, 2000) and Mittal et al. (2011) have initiated a study of error estimates En(f) through
trigonometric-Fourier approximation (tfa) for the situations in which the summability matrix T does not have monotone rows. In this paper, the first author continues the work in the direction for T to be a Np-matrix. We extend two theorems on summability matrix Np of Deger et al. (2012) where they have extended two theorems of Chandra (2002) using Cλ-method obtained by deleting a set of rows from Cesàro matrix C1. Our theorems also generalize two theorems of Leindler (2005) to Np-matrix which in turn generalize the result of Chandra (2002) and Quade (1937)
Highly scalable solution of incompressible Navier-Stokes equations using the spectral element method with overlapping grids
No full textWe present a highly-flexible Schwarz overlapping framework for simulating turbulent fluid/thermal transport in complex domains. The approach is based on a variant of the Schwarz alternating method in which the solution is advanced in parallel in separate overlapping subdomains. In each domain, the governing equations are discretized with an efficient high-order spectral element method (SEM). At each step, subdomain boundary data are determined by interpolating from the overlapping region of adjacent subdomains. The data are either lagged in time or extrapolated to higher-order temporal accuracy using a novel stabilized predictor-corrector algorithm. Matrix stability analysis is used to determine the optimal number of corrector iterations. Stability and accuracy are further improved with an optimal mass flux correction to guarantee mass conservation throughout the domain. The method supports an arbitrary number of subdomains. A new multirate time-stepping scheme is developed (a first for incompressible flow simulations) that allows the underlying equations to be advanced with time-step sizes varying as much as an order-of-magnitude between adjacent domains. All the developments maintain the third-order temporal convergence and exponential convergence of the originating SEM framework. This dissertation also presents a mesh optimizer that has been specifically designed for meshes generated for turbulent flow problems. The optimizer supports surface mesh improvement, which minimizes geometrical approximation errors. The smoother is shown to reduce the computational cost of numerical calculations by as much as 40%. Numerous examples illustrate the effectiveness of these new technologies for analyzing challenging turbulence problems that were previously infeasible.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-12-01The student, Ketan Mittal, accepted the attached license on 2019-10-07 at 11:58.The student, Ketan Mittal, submitted this Dissertation for approval on 2019-10-07 at 12:08.This Dissertation was approved for publication on 2019-10-09 at 15:36.DSpace SAF Submission Ingestion Package generated from Vireo submission #14486 on 2020-02-28 at 17:20:54Made available in DSpace on 2020-03-02T22:12:10Z (GMT). No. of bitstreams: 2
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Role of the Multidisciplinary Team (MDT) Meetings in Rectal Cancer Management
No full textThe management of rectal cancer is complex and requires the expertise of multiple disciplines and various treatment modalities. Multidisciplinary team (MDT) discussions are essential for the optimal management of patients with rectal cancer
Evidence-Based Surgery: Knowledge, Attitudes, and Perceived Barriers among Surgical Trainees
No full text- …
