Fairness in Machine Learning meets with Equity in Healthcare

With the growing utilization of machine learning in healthcare, there is increasing potential to enhance healthcare outcomes. However, this also brings the risk of perpetuating biases in data and model design that can harm certain demographic groups based on factors such as age, gender, and race. This study proposes an artificial intelligence framework, grounded in software engineering principles, for identifying and mitigating biases in data and models while ensuring fairness in healthcare settings. A case study is presented to demonstrate how systematic biases in data can lead to amplified biases in model predictions, and machine learning methods are suggested to prevent such biases. Future research aims to test and validate the proposed ML framework in real-world clinical settings to evaluate its impact on promoting health equity.Comment: Accepted in Association for the Advancement of Artificial Intelligence (AAAI) 2023 , Responsible Medical AI, Design, and Operationalization Symposiu

BERT4Loc: BERT for Location -- POI Recommender System

Recommending points of interest is a difficult problem that requires precise location information to be extracted from a location-based social media platform. Another challenging and critical problem for such a location-aware recommendation system is modelling users' preferences based on their historical behaviors. We propose a location-aware recommender system based on Bidirectional Encoder Representations from Transformers for the purpose of providing users with location-based recommendations. The proposed model incorporates location data and user preferences. When compared to predicting the next item of interest (location) at each position in a sequence, our model can provide the user with more relevant results. Extensive experiments on a benchmark dataset demonstrate that our model consistently outperforms a variety of state-of-the-art sequential models

NBIAS: A Natural Language Processing Framework for Bias Identification in Text

Bias in textual data can lead to skewed interpretations and outcomes when the data is used. These biases could perpetuate stereotypes, discrimination, or other forms of unfair treatment. An algorithm trained on biased data ends up making decisions that disproportionately impact a certain group of people. Therefore, it is crucial to detect and remove these biases to ensure the fair and ethical use of data. To this end, we develop a comprehensive and robust framework \textsc{Nbias} that consists of a data layer, corpus contruction, model development layer and an evaluation layer. The dataset is constructed by collecting diverse data from various fields, including social media, healthcare, and job hiring portals. As such, we applied a transformer-based token classification model that is able to identify bias words/ phrases through a unique named entity. In the assessment procedure, we incorporate a blend of quantitative and qualitative evaluations to gauge the effectiveness of our models. We achieve accuracy improvements ranging from 1% to 8% compared to baselines. We are also able to generate a robust understanding of the model functioning, capturing not only numerical data but also the quality and intricacies of its performance. The proposed approach is applicable to a variety of biases and contributes to the fair and ethical use of textual data.Comment: Under revie

3D DRUG PRINTING- A SWING FROM LABORATORY PRODUCTION TO COMPUTERIZED PRODUCTION

Three-Dimensional (3D) printing is a process where objects are made in successive layers under computer control by fusing or depositing materials. The objects can be of nearly any shape or geometry and come in a computer-aided (CAD) design from 3D model. Since 3D printing began in 1984, it has changed enormously and has been used in a wide range of fields, including medicine and architecture. 3D printing moves rapidly and in future will transform and change the way we live and work from laboratory-based organs to pharmaceutical supplies. 3D printing in pharmaceuticals has been used to produce many novel dosage forms like microcapsules, complex drug-release profiles, nanosuspensions, and multilayered drug delivery devices. It also offers important advantages from the industrial point of view such as cost-efficiency, higher productivity, democracy-making and enhanced cooperation. Keeping in view the recent approval given by USFDA to many drug the focus has now shifted to the personalized medicine as it offers an important benefit to patients who need medications that have narrow therapeutic index or a higher predilection to be influenced by genetic polymorphisms. 3D printer is now seen as a valuable, efficient and economical tool to manufacture individualized medications, tailored to specific patients based on their needs and thereby change the future of pharmacy practice in general and pharmaceutical care in particular

Comparative bioavailability analysis of oral alendronate sodium formulations in Pakistan

Alendronate sodium, a bisphosphonate drug, it is used to treat osteoporosis and other bone diseases. The present study was designed to conduct comparative bioavailability analysis of oral formulations of alendronate sodium through an open-label, randomized, 2-sequence, 2-period crossover study. Healthy adult male Pakistani volunteers received a single 70 mg dose of the test or reference formulation of alendronate sodium followed by a 7 day washout period. Plasma drug concentrations were determined using a validated HPLC post column fluorescence derivatization method. AUC0-t, AUC0-8, Cmax and Tmax were determined by non-compartmental analysis and were found within the permitted range of 80% to 125% set by the US Food and Drug Administration (FDA). Results show that both in vitro and in vivo assays of all test brands were within the specification of the US Pharmacopoeial limits and were statistically bioequivalent. No adverse events were reported in this study

An Efficient Channel Access Scheme for Vehicular Ad Hoc Networks

Vehicular Ad Hoc Networks (VANETs) are getting more popularity due to the potential Intelligent Transport Systems (ITS) technology. It provides many efficient network services such as safety warnings (collision warning), entertainment (video and voice), maps based guidance, and emergency information. VANETs most commonly use Road Side Units (RSUs) and Vehicle-to-Vehicle (V2V) referred to as Vehicle-to-Infrastructure (V2I) mode for data accessing. IEEE 802.11p standard which was originally designed for Wireless Local Area Networks (WLANs) is modified to address such type of communication. However, IEEE 802.11p uses Distributed Coordination Function (DCF) for communication between wireless nodes. Therefore, it does not perform well for high mobility networks such as VANETs. Moreover, in RSU mode timely provision of data/services under high density of vehicles is challenging. In this paper, we propose a RSU-based efficient channel access scheme for VANETs under high traffic and mobility. In the proposed scheme, the contention window is dynamically varied according to the times (deadlines) the vehicles are going to leave the RSU range. The vehicles with shorter time deadlines are served first and vice versa. Simulation is performed by using the Network Simulator (NS-3) v. 3.6. The simulation results show that the proposed scheme performs better in terms of throughput, backoff rate, RSU response time, and fairness

OCULAR INSERTS - A NOVEL APPROACH IN OCULAR DRUG DELIVERY

Among the ocular dosage forms, the physiological and anatomical constraints put forth by the eye is a significant challenge to the pharmaceutical scientists and researchers to target drugs to the posterior segment of the eye, prolong their contact time with the ocular surface and sustained release. Hence novel drug delivery strategies and formulations are to be developed and explored which will overcome the ocular constraints and provide better patient compliance. At present, various novel and controlled drug delivery systems are being developed in order to attain better ocular bioavailability, sustained action of ocular drugs as well as good patient compliance. Ocular insert is an example of such delivery system. These are sterile preparations, with a thin, multilayered, drug-impregnated, solid or semisolid consistency devices placed into cul-de-sac or conjunctiva sac of the eye. Ocular inserts are an alternative approach to overcome the problems associated with conventional ocular dosage forms like solutions, suspensions, ointments, etc. The article hereunder gives a detailed idea about the classification, mechanism of action, formulation, pros and cons; evaluation and future trends of ocular inserts

Formulation and Evaluation of Sustained release tablets of Venlafaxine HCl

The aim of the present study was to develop a tablet formulation for sustained release of venlafaxine HCl. Control or sustained release formulations have great applications in improving the physicochemical properties and the pharmacokinetic profile of the drugs. Carbopol tablets containing venlafaxine HCl were developed successfully by wet granulation technique. The tablets were evaluated for matrix integrity and drug release in 0.1 N HCl using USP II dissolution apparatus maintained at optimum conditions. The developed tablets were robust and possessed excellent physicochemical properties. The tablets showed great matrix integrity and withstood the hydrodynamic environment of the dissolution medium for > 12 hours. The hydration and swelling behaviour of the tablets was excellent. It was found that the swelling characteristics of the tablets depended on the amount of the polymer used in the tablets as well as the polymer/drug ratio. The tablets provided more than 90% drug release over a period of 12 hours. The drug release data was subjected to kinetic dissolution modelling. It was found that the drug release from the tablets followed Korsmeyer-Peppas model of drug release. This suggests that the mechanism of the drug release from the formulations may be both diffusion as well as polymer erosion. Keywords: Sustained release, Carbopol, Venlafaxine HC