Leveraging ANFIS with Adam and PSO optimizers for Parkinson's disease.

Parkinson's disease (PD) is an age-related neurodegenerative disorder characterized by motor deficits, including tremor, rigidity, bradykinesia, and postural instability. According to the World Health Organization, about 1 % of the global population has been diagnosed with PD, and this figure is expected to double by 2040. Early and accurate diagnosis of PD is critical to slowing down the progression of the disease and reducing long-term disability. Due to the complexity of the disease, it is difficult to accurately diagnose it using traditional clinical tests. Therefore, it has become necessary to develop intelligent diagnostic models that can accurately detect PD. This article introduces a novel hybrid approach for accurate prediction of PD using an ANFIS with two optimizers, namely Adam and PSO. ANFIS is a type of fuzzy logic system used for nonlinear function approximation and classification, while Adam optimizer has the ability to adaptively adjust the learning rate of each individual parameter in an ANFIS at each training step, which helps the model find a better solution more quickly. PSO is a metaheuristic approach inspired by the behavior of social animals such as birds. Combining these two methods has potential to provide improved accuracy and robustness in PD diagnosis compared to existing methods. The proposed method utilized the advantages of both optimization techniques and applied them on the developed ANFIS model to maximize its prediction accuracy. This system was developed by using an open access clinical and demographic data. The chosen parameters for the ANFIS were selected through a comparative experimental analysis to optimize the model considering the number of fuzzy membership functions, number of epochs of ANFIS, and number of particles of PSO. The performance of the two ANFIS models: ANFIS (Adam) and ANFIS (PSO) focusing at ANFIS parameters and various evaluation metrics are further analyzed in detail and presented, The experimental results showed that the proposed ANFIS (PSO) shows better results in terms of loss and precision, whereas, the ANFIS (Adam) showed the better results in terms of accuracy, f1-score and recall. Thus, this adaptive neural-fuzzy algorithm provides a promising strategy for the diagnosis of PD, and show that the proposed models show their suitability for many other practical applications.

Community action for people with HIV and sex workers during the COVID-19 pandemic in India.

Sex workers have been one of the marginalized groups that have been particularly affected by India's stringent lockdown in response to the coronavirus disease 2019 (COVID-19) pandemic. The sudden loss of livelihood and lack of access to health care and social protection intensified the vulnerabilities of sex workers, especially those living with HIV. In response, Ashodaya Samithi, an organization of more than 6000 sex workers, launched an innovative programme of assistance in four districts in Karnataka. Since access to antiretroviral therapy (ART) was immediately disrupted, Ashodaya adapted its HIV outreach programme to form an alternative, community-led system of distributing ART at discreet, private sites. WhatsApp messaging was used to distribute information on accessing government social benefits made available in response to the COVID-19 pandemic. Other assistance included advisory messages posted in WhatsApp groups to raise awareness, dispel myths and mitigate violence, and regular, discreet phone check-ins to follow up on the well-being of members. The lessons learnt from these activities represent an important opportunity to consider more sustainable approaches to the health of marginalized populations that can enable community organizations to be better prepared to respond to other public health crises as they emerge.

Bio-inspired dimensionality reduction for Parkinson's disease (PD) classification.

Given the demand for developing the efficient Machine Learning (ML) classification models for healthcare data, and the potentiality of Bio-Inspired Optimization (BIO) algorithms to tackle the problem of high dimensional data, we investigate the range of ML classification models trained with the optimal subset of features of PD data set for efficient PD classification. We used two BIO algorithms, Genetic Algorithm (GA) and Binary Particle Swarm Optimization (BPSO), to determine the optimal subset of features of PD data set. The data set chosen for investigation comprises 756 observations (rows or records) taken over 755 attributes (columns or dimensions or features) from 252 PD patients. We employed MaxAbsolute feature scaling method to normalize the data and one hold cross-validation method to avoid biased results. Accordingly, the data is split in to training and testing set in the ratio of 70% and 30%. Subsequently, we employed GA and BPSO algorithms separately on 11 ML classifiers (Logistic Regression (LR), linear Support Vector Machine (lSVM), radial basis function Support Vector Machine (rSVM), Gaussian Naïve Bayes (GNB), Gaussian Process Classifier (GPC), k-Nearest Neighbor (kNN), Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Ada Boost (AB) and Quadratic Discriminant Analysis (QDA)), to determine the optimal subset of features (reduction of dimensionality) contributing to the highest classification accuracy. Among all the bio-inspired ML classifiers employed: GA-inspired MLP produced the maximum dimensionality reduction of 52.32% by selecting only 359 features and delivering 85.1% of the classification accuracy; GA-inspired AB delivered the maximum classification accuracy of 90.7% producing the dimensionality reduction of 41.43% by selecting only 441 features; And, BPSO-inspired GNB produced the maximum dimensionality reduction of 47.14% by selecting 396 features and delivering the classification accuracy of 79.3%; BPSOMLP delivered the maximum classification accuracy of 89% and produced 46.48% of the dimensionality reduction by selecting only 403 features.

The Ashodaya PrEP project: Lessons and implications for scaling up PrEP from a community-led demonstration project among female sex workers in Mysore, India.

To inform PrEP roll out, Ashodaya Samithi, a sex workers' collective, conducted a community-led prospective demonstration project among female sex workers in Mysore and Mandya, India. Following a community preparedness phase and pre-screening, participants were recruited for clinical screening and enrolment, provided PrEP as part of combination HIV prevention, and followed for 16 months. Adherence was measured by self-reported pill intake and by tenofovir blood level testing among a subset of participants. Of the 647 participants enrolled, 640 completed follow-up. Condom use remained stable and no HIV seroconversions occurred. Self-reported daily PrEP intake over the last month was 97.97% at the end of the study. Tenofovir blood levels >40 ng/mL (consistent with steady state dosing) were detected among 80% (n = 68/85) and 90.48% (n = 76/84) of participants at month 3 and 6, respectively. Our study holds important insights for rolling out PrEP in community settings as part of targeted HIV prevention interventions.

Beyond internalised stigma: daily moralities and subjectivity among self-identified kothis in Karnataka, South India.

The Bill and Melinda Gates Foundation has poured a tremendous amount of resources into epidemic prevention in India's high HIV prevalence zones, through their Avahan initiative. These community-centred programmes operate under the assumption that fostering community-based organisational development and empowering the community to take charge of HIV prevention and education will help to transform the wider social inequalities that inhibit access to health services. Focusing on the South Indian state of Karnataka, this paper explores a troubling set of local narratives that, we contend, hold broader implications for future programme planning and implementation. Although confronting stigma and discrimination has become a hallmark in community mobilisation discourse, communities of self-identified kothis (feminine men) who were involved in Avahan programme activities continued to articulate highly negative attitudes about their own sexualities in relation to various spheres of social life. Rather than framing an understanding of these narratives in psychological terms of 'internalized stigma', we draw upon medical anthropological approaches to the study of stigma that emphasise how social, cultural and moral processes create stigmatising conditions in the everyday lives of people. The way stigma continues to manifest itself in the self-perceptions of participants points to an area that warrants critical public health attention.

Sex in the city: privacy-making practices, spatialized intimacies and the environmental risks of men-who-have-sex-with-men in South India.

Employing community-based approaches, the spatialization of sexual risk among men-who-have-sex-with-men (MSM) at local cruising spots was explored in South India. To move beyond individualistic and structural deterministic understandings of sexual risk the study examined how erotic associations and networks formed and dissolved as social actors connect to each other through their material world (which includes other bodies). Crowding was important for safely establishing intimacy in public but also created contexts of discrimination and violence, particularly for feminine-acting males. Risk itineraries drawn by MSM anticipated fluctuating levels of risk, enabling them to avoid dangerous situations. Although sexual typologies connected gender nonconforming males to HIV prevention networks, they reinforce the exclusion of men who did not identify with sexual minority identities. Future work must therefore address the HIV prevention needs of men whose identities cannot be readily separated from "the general population".

From individuals to complex systems: exploring the sexual networks of men who have sex with men in three cities of Karnataka, India.

INTRODUCTION: Research on the HIV vulnerability of men who have sex with men (MSM) in India has tended to focus on aggregates of individual risk behaviours. However, such an approach often overlooks the complexities in the sexual networks that ultimately underpin patterns of spread. This paper analyses a set of sexual contact network (SCN) snapshots in relation to ethnographic findings to reorientate individual-level explanations of risk behaviour in terms of more complex systems. METHODS: Fifteen community researchers conducted a 2-month ethnographic study in three cities in Karnataka to generate descriptions of the risk environments inhabited by MSM. SCNs were reconstructed by two methods. First, initial participants, defined as nodes of various sexual networks, were purposively sampled. In each site, six nodes brought in three sexual partners separately as participants. In all sites, 72 participants completed 431 surveys for their 7-day sexual partners. Second, each site determined four groups representing various sexual networks, each group containing four individuals. In all sites, 48 participants completed 334 surveys for their regular sexual partner. RESULTS: Considerable differences were observed between sites for practically all included behavioural variables. On their own, these characteristics yielded contradictory interpretations with respect to understanding contrasts in HIV prevalence at each site. However, viewing these variables in relation to SCNs and ethnographic data produced non-linear interpretations of HIV vulnerability which suggested importance to local interventions. CONCLUSION: SCN data may be used with existing data on risk behaviour and the structural determinants of vulnerability to re-tailor more tightly focused interventions.

On becoming a male sex worker in Mysore: sexual subjectivity, "empowerment," and community-based HIV prevention research.

Growing public health attention has been placed on the HIV vulnerability of males who sell sex to males in India. However, there is little research that outlines the trajectories through which males come to be involved in practicing sex work in India. Locating "male sex work" within a vibrant social, political, and erotic landscape, this article explores the intertwining of "sexual subjectivity" and "sex work." The authors refer to 70 sexual life histories generated from research conducted in Mysore to unsettle dominant public health notions that regard male sex work as rooted solely in poverty or as a decontexualized "behavioral risk factor." Such perspectives are countered by demonstrating how male sex work in Mysore encompasses a complex interplay between self-realization, sexual desire, social interaction, and public health discourse. Local conceptualizations of selfhood are discussed to suggest the limitations of prevailing empowerment discourses that advance Western notions of individuality.