Uncovering Bias: Exploring Machine Learning Techniques for Detecting and Mitigating Bias in Data – A Literature Review

The presence of Bias in models developed using machine learning algorithms has emerged as a critical issue. This literature review explores the topic of uncovering the existence of bias in data and the application of techniques for detecting and mitigating Bias. The review provides a comprehensive analysis of the existing literature, focusing on pre-processing techniques, post-pre-processing techniques, and fairness constraints employed to uncover and address the existence of Bias in machine learning models. The effectiveness, limitations, and trade-offs of these techniques are examined, highlighting their impact on advocating fairness and equity in decision-making processes. The methodology consists of two key steps: data preparation and bias analysis, followed by machine learning model development and evaluation. In the data preparation phase, the dataset is analyzed for biases and pre-processed using techniques like reweighting or relabeling to reduce bias. In the model development phase, suitable algorithms are selected, and fairness metrics are defined and optimized during the training process. The models are then evaluated using performance and fairness measures and the best-performing model is chosen. The methodology ensures a systematic exploration of machine learning techniques to detect and mitigate bias, leading to more equitable decision-making. The review begins by examining the techniques of pre-processing, which involve cleaning the data, selecting the features, feature engineering, and sampling. These techniques play an important role in preparing the data to reduce bias and promote fairness in machine learning models. The analysis highlights various studies that have explored the effectiveness of these techniques in uncovering and mitigating bias in data, contributing to the development of more equitable and unbiased machine learning models. Next, the review delves into post-pre-processing techniques that focus on detecting and mitigating bias after the initial data preparation steps. These techniques include bias detection methods that assess the disparate impact or disparate treatment in model predictions, as well as bias mitigation techniques that modify model outputs to achieve fairness across different groups. The evaluation of these techniques, their performance metrics, and potential trade-offs between fairness and accuracy are discussed, providing insights into the challenges and advancements in bias mitigation. Lastly, the review examines fairness constraints, which involve the imposition of rules or guidelines on machine learning algorithms to ensure fairness in predictions or decision-making processes. The analysis explores different fairness constraints, such as demographic parity, equalized odds, and predictive parity, and their effectiveness in reducing bias and advocating fairness in machine learning models. Overall, this literature review provides a comprehensive understanding of the techniques employed to uncover and mitigate the existence of bias in machine learning models. By examining pre-processing techniques, post-pre-processing techniques, and fairness constraints, the review contributes to the development of more fair and unbiased machine learning models, fostering equity and ethical decision-making in various domains. By examining relevant studies, this review provides insights into the effectiveness and limitations of various pre-processing techniques for bias detection and mitigation via Pre-processing, Adversarial learning, Fairness Constraints, and Post-processing techniques

An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate

Why women choose to give birth at home: a situational analysis from urban slums of Delhi

Objectives: Increasing institutional births is an important strategy for attaining Millennium Development Goal -5. However, rapid growth of low income and migrant populations in urban settings in low-income and middle-income countries, including India, presents unique challenges for programmes to improve utilisation of institutional care. Better understanding of the factors influencing home or institutional birth among the urban poor is urgently needed to enhance programme impact. To measure the prevalence of home and institutional births in an urban slum population and identify factors influencing these events. Design: Cross-sectional survey using quantitative and qualitative methods. Setting: Urban poor settlements in Delhi, India. Participants: A house-to-house survey was conducted of all households in three slum clusters in north-east Delhi (n=32 034 individuals). Data on birthing place and sociodemographic characteristics were collected using structured questionnaires (n=6092 households). Detailed information on pregnancy and postnatal care was obtained from women who gave birth in the past 3 months (n=160). Focus group discussions and in-depth interviews were conducted with stakeholders from the community and healthcare facilities. Results: Of the 824 women who gave birth in the previous year, 53% (95% CI 49.7 to 56.6) had given birth at home. In adjusted analyses, multiparity, low literacy and migrant status were independently predictive of home births. Fear of hospitals (36%), comfort of home (20.7%) and lack of social support for child care (12.2%) emerged as the primary reasons for home births. Conclusions: Home births are frequent among the urban poor. This study highlights the urgent need for improvements in the quality and hospitality of client services and need for family support as the key modifiable factors affecting over two-thirds of this population. These findings should inform the design of strategies to promote institutional births

Reproductive healthcare utilization in urban poor settlements of Delhi: Baseline survey of ANCHUL (Ante Natal and Child Health care in Urban Slums) project

Background: Disparity in utilization of reproductive healthcare services between the urban poor and the urban non-poor households in the developing nations is well known. However, disparity may also exist within urban poor households. Our objective was to document the extent of disparity in reproductive healthcare utilization among the urban poor and to identify the socio-demographic determinants of underutilization with a view to characterizing this vulnerable subpopulation. Methods: A survey of 16,221 households was conducted in 39 clusters from two large urban poor settlements in Delhi. From 13,451 consenting households, socio-demographic data and information on births, maternal and child deaths within the previous year was collected. Details of antenatal care (ANC) was collected from 597 pregnant women. Information on ANC and postnatal care was also obtained from 596 recently delivered (within six months) mothers. All data were captured electronically using a customized and validated smart phone application. Households were categorized into quintiles of socio-economic position (SEP) based on dwelling characteristics and possession of durable assets using principal component analysis. Potential socio-demographic determinants of reproductive healthcare utilization were examined using random effects logistic regression. Results: The prevalence of facility based birthing was 77 % (n = 596 mothers). Of the 596 recently delivered mothers only 70 % had an ANC registration card, 46.3 % had ANC in their first trimester, 46 % had visited a facility within 4 weeks post-delivery and 27 % were using modern contraceptive methods. Low socio-economic position was the most important predictor of underutilization with a clear gradient across SEP quintiles. Compared to the poorest, the least poor women were more likely to be registered for ANC (OR 1.96, 95 %CI 0.95-4.15) and more likely to have made ≥ 4 ANC visits (OR 5.86, 95 %CI 2.82-12.19). They were more likely to have given birth in a facility (OR 4.87, 95 %CI 2.12-11.16), to have visited a hospital within one month of childbirth (OR 3.18, 95 %CI 1.62-6.26). In general, government funded health insurance and conditional cash transfers schemes were underutilized in this community. Conclusion: The poorest segment of the urban poor population utilizes reproductive healthcare facilities the least. Strategies to improve access and utilization of healthcare services among the poorest of the poor may be necessary to achieve universal health coverage. Electronic supplementary material The online version of this article (doi:10.1186/s12884-015-0635-8) contains supplementary material, which is available to authorized users

Improved outcomes in stroke thrombolysis with pre-specified imaging criteria

Background: A 1995 National Institute of Neurological Disorders (NINDS) study found benefit for intravenous tissue plasminogen activator (tPA) in acute ischemic stroke (AIS). The symptomatic intracranial hemorrhage (SICH) rate in the NINDS study was 6.4%, which may be deterring some physicians from using this medication. Methods: Starting December 1, 1998, patients with AIS in London, Ontario were treated according to NINDS criteria with one major exception; those with approximately greater than one-third involvement of the idealized middle cerebral artery (MCA) territory on neuroimaging were excluded from treatment. The method used to estimate involvement of one-third MCA territory involvement bears the acronym ICE and had a median kappa value of 0.80 among five physicians. Outcomes were compared to the NINDS study. Results: Between December 1, 1998 and February 1,2000, 30 patients were treated. Compared to the NINDS study, more London patients were treated after 90 minutes (p\u3c0.00001) and tended to be older. No SICH was observed. Compared to the treated arm of the NINDS trial, fewer London patients were dead or severely disabled at three months (p=0.04). Compared to the placebo arm of the trial, more patients made a partial recovery at 24 hours (p=0.02), more had normal outcomes (p=0.03) and fewer were dead or severely disabled at three months (p=0.004). Conclusions: The results of the NINDS study were closely replicated and, in some instances, improved upon in this small series of Canadian patients, despite older age and later treatment. These findings suggest that imaging exclusion criteria may optimize the benefits of tPA

Association of antenatal care and place of delivery with newborn care practices: evidence from a cross-sectional survey in rural Uttar Pradesh, India

Background: Appropriate immediate newborn care is vital for neonatal survival. Antenatal period is a crucial time to impart knowledge and awareness to mothers regarding newborn care, either during facility visits or during home visits by community health workers (CHWs) especially in the rural context. In this paper, we report newborn care practices in rural Uttar Pradesh (UP) and have explored association between newborn care practices with antenatal care, contact with community health workers during pregnancy and place of childbirth. Methods: We use cross-sectional baseline data (which is part of a larger intervention project) collected from 129 gram panchayats (GPs) from 15 administrative blocks spread over five districts of UP in 2013. From currently married women (n = 2208) of 15\u201349 years, who delivered 15 months prior to the survey, we collected information on women\u2019s demographic and socio-economic characteristics, knowledge and practice of reproductive, maternal, newborn, child health and nutrition behaviours. Association of newborn practices with antenatal care, contacts by community health worker during pregnancy and place of childbirth were tested using random intercept logistic regression, adjusting for socio-economic and demographic factors and accounting for clustering at the GP and block levels. Results: Eighty-three percent of 2208 mothers received ANC, but only half of the respondents received a minimum of three ANC visits. More than two thirds of respondents delivered at a health facility. Practice of newborn care was poor: merely one fourth of women practised clean cord care, one third of women followed good breastfeeding practices (initiation with an hour of birth, fed colostrum and did not give pre-lacteal feeds) and one third provided adequate thermal care (kept baby warm and delayed bathing). Only 5% followed all above practices with evidence of clustering of newborn care practices at the block and GP levels. While facility-based childbirth was strongly associated with appropriate newborn care practices, ANC visits and contacts with CHWs was not associated with all newborn care practices. Conclusion: The quality of ANC care provided needs to be improved to have an impact on newborn care practices. Our finding emphasizes the importance of facility-based birthing. There is a need for training CHWs to strengthen their counselling skills on newborn care. Variation of newborn care practices between communities should be taken into consideration while implementing any intervention to optimize benefits

The challenges and opportunities of conducting a clinical trial in a low resource setting: The case of the Cameroon mobile phone SMS (CAMPS) trial, an investigator initiated trial

Conducting clinical trials in developing countries often presents significant ethical, organisational, cultural and infrastructural challenges to researchers, pharmaceutical companies, sponsors and regulatory bodies. Globally, these regions are under-represented in research, yet this population stands to gain more from research in these settings as the burdens on health are greater than those in developed resourceful countries. However, developing countries also offer an attractive setting for clinical trials because they often have larger treatment naive populations with higher incidence rates of disease and more advanced stages. These factors can present a reduction in costs and time required to recruit patients. So, balance needs to be found where research can be encouraged and supported in order to bring maximum public health benefits to these communities. The difficulties with such trials arise from problems with obtaining valid informed consent, ethical compensation mechanisms for extremely poor populations, poor health infrastructure and considerable socio-economic and cultural divides. Ethical concerns with trials in developing countries have received attention, even though many other non-ethical issues may arise. Local investigator initiated trials also face a variety of difficulties that have not been adequately reported in literature. This paper uses the example of the Cameroon Mobile Phone SMS trial to describe in detail, the specific difficulties encountered in an investigator-initiated trial in a developing country. It highlights administrative, ethical, financial and staff related issues, proposes solutions and gives a list of additional documentation to ease the organisational process

Identification of priority health conditions for field-based screening in urban slums in Bangalore, India

BACKGROUND: Urban slums are characterised by unique challenging living conditions, which increase their inhabitants' vulnerability to specific health conditions. The identification and prioritization of the key health issues occurring in these settings is essential for the development of programmes that aim to enhance the health of local slum communities effectively. As such, the present study sought to identify and prioritise the key health issues occurring in urban slums, with a focus on the perceptions of health professionals and community workers, in the rapidly growing city of Bangalore, India. METHODS: The study followed a two-phased mixed methods design. During Phase I of the study, a total of 60 health conditions belonging to four major categories: - 1) non-communicable diseases; 2) infectious diseases; 3) maternal and women's reproductive health; and 4) child health - were identified through a systematic literature review and semi-structured interviews conducted with health professionals and other relevant stakeholders with experience working with urban slum communities in Bangalore. In Phase II, the health issues were prioritised based on four criteria through a consensus workshop conducted in Bangalore. RESULTS: The top health issues prioritized during the workshop were: diabetes and hypertension (non-communicable diseases category), dengue fever (infectious diseases category), malnutrition and anaemia (child health, and maternal and women's reproductive health categories). Diarrhoea was also selected as a top priority in children. These health issues were in line with national and international reports that listed them as top causes of mortality and major contributors to the burden of diseases in India. CONCLUSIONS: The results of this study will be used to inform the development of technologies and the design of interventions to improve the health outcomes of local communities. Identification of priority health issues in the slums of other regions of India, and in other low and lower middle-income countries, is recommended

Multi-center feasibility study evaluating recruitment, variability in risk factors and biomarkers for a diet and cancer cohort in India

<p>Abstract</p> <p>Background</p> <p>India's population exhibits diverse dietary habits and chronic disease patterns. Nutritional epidemiologic studies in India are primarily of cross-sectional or case-control design and subject to biases, including differential recall of past diet. The aim of this feasibility study was to evaluate whether a diet-focused cohort study of cancer could be established in India, providing insight into potentially unique diet and lifestyle exposures.</p> <p>Methods</p> <p>Field staff contacted 7,064 households within three regions of India (New Delhi, Mumbai, and Trivandrum) and found 4,671 eligible adults aged 35-69 years. Participants completed interviewer-administered questionnaires (demographic, diet history, physical activity, medical/reproductive history, tobacco/alcohol use, and occupational history), and staff collected biological samples (blood, urine, and toenail clippings), anthropometric measurements (weight, standing and sitting height; waist, hip, and thigh circumference; triceps, sub-scapula and supra-patella skin fold), and blood pressure measurements.</p> <p>Results</p> <p>Eighty-eight percent of eligible subjects completed all questionnaires and 67% provided biological samples. Unique protein sources by region were fish in Trivandrum, dairy in New Delhi, and pulses (legumes) in Mumbai. Consumption of meat, alcohol, fast food, and soft drinks was scarce in all three regions. A large percentage of the participants were centrally obese and had elevated blood glucose levels. New Delhi participants were also the least physically active and had elevated lipids levels, suggesting a high prevalence of metabolic syndrome.</p> <p>Conclusions</p> <p>A high percentage of participants complied with study procedures including biological sample collection. Epidemiologic expertise and sufficient infrastructure exists at these three sites in India to successfully carry out a modest sized population-based study; however, we identified some potential problems in conducting a cohort study, such as limited number of facilities to handle biological samples.</p