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

Networkless Mobile Payments With Minimal changes in Trusted Execution Environments

Peer-to-peer mobile digital payments can be made in the absence of a network as follows: the receiver of funds verifies the availability of on-device balance by examining the prior, authenticated, transaction records of the sender. A new transaction record including the transaction amount is created, made immutable and secure using cryptographic techniques, and is stored at both sender and receiver. When either sender or receiver regains network connectivity, the transaction is settled with the original provider of the on-device balance, e.g., a financial institution. The integrity of the records of offline transactions, e.g., made in the absence of a mobile network, is vital for offline payments to be secure and trustworthy. This disclosure describes techniques that, with minimal modifications to trusted applications (TAs) in a trusted execution environment (TEE) to securely verify transaction records and to harden them against malicious attacks

Secure Mobile Payments Without Network Connectivity

Mobile payments depend on the availability of internet connectivity, e.g., to enable a centralized service to authenticate a payment. This disclosure describes techniques to enable peer-to-peer mobile payments in the absence of a network. A user has an initial amount, referred to as the balance, that is transferred to their mobile device from a balance provider, e.g., a financial institution. The balance is digitally signed by both the user and the balance provider. To transact in the absence of a network, peer users perform a contactless payment as follows. The receiver of funds verifies the availability of funds by examining the prior, authenticated, transaction records of the sender. A transaction record including the transaction amount is created and made immutable and secure using cryptographic techniques. When either the sender or receiver regains network connectivity, the transaction is settled with the balance provider. Double-spend attempts by a malicious sender are forestalled by enabling secure maintenance of the true balance on a sender’s device (even in the absence of a network), and by enabling the receiver to settle with the sender’s balance provider on the basis of an authenticated transaction record

Distinct enhancers at the Pax3 locus can function redundantly to regulate neural tube and neural crest expressions

AbstractPax3 is a transcription factor expressed in somitic mesoderm, dorsal neural tube and pre-migratory neural crest during embryonic development. We have previously identified cis-acting enhancer elements within the proximal upstream genomic region of Pax3 that are sufficient to direct functional expression of Pax3 in neural crest. These elements direct expression of a reporter gene to pre-migratory neural crest in transgenic mice, and transgenic expression of a Pax3 cDNA using these elements is sufficient to rescue neural crest development in mice otherwise lacking endogenous Pax3. We show here that deletion of these enhancer sequences by homologous recombination is insufficient to abrogate neural crest expression of Pax3 and results in viable mice. We identify a distinct enhancer in the fourth intron that is also capable of mediating neural crest expression in transgenic mice and zebrafish. Our analysis suggests the existence of functionally redundant neural crest enhancer modules for Pax3

Electromagnetic Counterparts of Compact Object Mergers Powered by the Radioactive Decay of R-process Nuclei

The most promising astrophysical sources of kHz gravitational waves (GWs) are the inspiral and merger of binary neutron star(NS)/black hole systems. Maximizing the scientific return of a GW detection will require identifying a coincident electro-magnetic (EM) counterpart. One of the most likely sources of isotropic EM emission from compact object mergers is a supernova-like transient powered by the radioactive decay of heavy elements synthesized in ejecta from the merger. We present the first calculations of the optical transients from compact object mergers that self-consistently determine the radioactive heating by means of a nuclear reaction network; using this heating rate, we model the light curve with a one dimensional Monte Carlo radiation transfer calculation. For an ejecta mass ~1e-2 M_sun[1e-3 M_sun] the resulting light curve peaks on a timescale ~ 1 day at a V-band luminosity nu L_nu ~ 3e41[1e41] ergs/s (M_V = -15[-14]); this corresponds to an effective "f" parameter ~3e-6 in the Li-Paczynski toy model. We argue that these results are relatively insensitive to uncertainties in the relevant nuclear physics and to the precise early-time dynamics and ejecta composition. Due to the rapid evolution and low luminosity of NS merger transients, EM counterpart searches triggered by GW detections will require close collaboration between the GW and astronomical communities. NS merger transients may also be detectable following a short-duration Gamma-Ray Burst or "blindly" with present or upcoming optical transient surveys. Because the emission produced by NS merger ejecta is powered by the formation of rare r-process elements, current optical transient surveys can directly constrain the unknown origin of the heaviest elements in the Universe.Comment: 14 pages, 7 figures; accepted to MNRAS; title changed to highlight r-process connection and new figure added

Executive Summary:International Clinical Practice Guidelines for Pediatric Ventilator Liberation, A Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network Document

Rationale: Pediatric-specific ventilator liberation guidelines are lacking despite the many studies exploring elements of extubation readiness testing. The lack of clinical practice guidelines has led to significant and unnecessary variation in methods used to assess pediatric patients’ readiness for extubation. Methods: Twenty-six international experts comprised a multiprofessional panel to establish pediatrics-specific ventilator liberation clinical practice guidelines, focusing on acutely hospitalized children receiving invasive mechanical ventilation for more than 24 hours. Eleven key questions were identified and first prioritized using the Modified Convergence of Opinion on Recommendations and Evidence. A systematic review was conducted for questions that did not meet an a priori threshold of &gt;80% agreement, with Grading of Recommendations, Assessment, Development, and Evaluation methodologies applied to develop the guidelines. The panel evaluated the evidence and drafted and voted on the recommendations. Measurements and Main Results: Three questions related to systematic screening using an extubation readiness testing bundle and a spontaneous breathing trial as part of the bundle met Modified Convergence of Opinion on Recommendations criteria of &gt;80% agreement. For the remaining eight questions, five systematic reviews yielded 12 recommendations related to the methods and duration of spontaneous breathing trials, measures of respiratory muscle strength, assessment of risk of postextubation upper airway obstruction and its prevention, use of postextubation noninvasive respiratory support, and sedation. Most recommendations were conditional and based on low to very low certainty of evidence. Conclusions: This clinical practice guideline provides a conceptual framework with evidence-based recommendations for best practices related to pediatric ventilator liberation.</p

Executive Summary: International Clinical Practice Guidelines for Pediatric Ventilator Liberation, A PALISI Network Document

RATIONALE: Pediatric specific ventilator liberation guidelines are lacking despite the many studies exploring elements of extubation readiness testing. The lack of clinical practice guidelines has led to significant and unnecessary variation in methods used to assess pediatric patients' readiness for extubation. METHODS: Twenty-six international experts comprised a multi-professional panel to establish pediatric specific ventilator liberation clinical practice guidelines, focusing on acutely hospitalized children receiving invasive mechanical ventilation for more than 24 hours. Eleven key questions were identified and first prioritized using the Modified Convergence of Opinion on Recommendations and Evidence. Systematic review was conducted for questions which did not meet an a-priori threshold of ≥80% agreement, with Grading of Recommendations, Assessment, Development, and Evaluation methodologies applied to develop the guidelines. The panel evaluated the evidence, drafted, and voted on the recommendations. MEASUREMENTS AND MAIN RESULTS: Three questions related to systematic screening, using an extubation readiness testing bundle and use of a spontaneous breathing trial as part of the bundle met Modified Convergence of Opinion on Recommendations criteria of ≥80% agreement. For the remaining 8 questions, 5 systematic reviews yielded 12 recommendations related to the methods and duration of spontaneous breathing trials; measures of respiratory muscle strength; assessment of risk of post-extubation upper airway obstruction and its prevention; use of post-extubation non-invasive respiratory support; and sedation. Most recommendations were conditional and based on low to very low certainty of evidence. CONCLUSION: This clinical practice guideline provides a conceptual framework with evidence-based recommendations for best practices related to pediatric ventilator liberation.The project was funded by Eunice Kennedy Shriver National Institute of Child Health (NICHD) and Human Development National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) (R13HD102137), in addition to funds from department of pediatrics at Indiana University School of Medicine, Indianapolis, Indiana