American Journal Of Biomedical Science & Pharmaceutical Innovation

Bias, Fairness, and Ethical Accountability in Machine Learning Systems: A Comprehensive Socio-Technical Analysis

Dr. Jonathan R. Whitaker — 2026-02-01

The rapid integration of machine learning systems into critical domains such as healthcare, education, finance, governance, and business decision-making has intensified scholarly and societal concern regarding bias, fairness, and ethical accountability. While algorithmic systems are often positioned as neutral or objective instruments, extensive research demonstrates that they frequently reproduce, amplify, or conceal existing social inequalities embedded within data, design choices, and institutional contexts. This article presents an extensive and theoretically grounded examination of bias and fairness in machine learning, situating technical challenges within broader socio-ethical, legal, and historical frameworks. Drawing extensively on interdisciplinary scholarship, this study conceptualizes algorithmic bias as a multi-layered phenomenon arising from data generation processes, modeling assumptions, deployment environments, and feedback loops. Central to this analysis is the synthesis of established taxonomies of bias and fairness, with particular emphasis on comprehensive frameworks articulated in the machine learning literature, including foundational surveys that systematize sources of bias, formal fairness definitions, and mitigation strategies (Mehrabi et al., 2021).

The article critically traces the evolution of algorithmic decision-making, highlighting how early optimism surrounding automation has given way to empirical evidence of disparate impacts across gender, race, socioeconomic status, and geographic context. Through a qualitative, literature-driven methodological approach, this work examines empirical findings from healthcare, education, cybersecurity, and business analytics to illustrate how fairness failures manifest in practice. The analysis further interrogates the limitations of purely technical solutions, arguing that fairness cannot be reduced to mathematical constraints alone but must be understood as a normative, context-dependent concept shaped by social values, regulatory regimes, and power relations. Regulatory instruments such as data protection laws and emerging AI governance frameworks are examined as partial but necessary responses to algorithmic harm.

The discussion advances a socio-technical model of ethical AI that integrates transparency, accountability, participatory design, and institutional oversight. By comparing divergent scholarly perspectives, the article reveals persistent tensions between accuracy and equity, innovation and regulation, and global ethical aspirations versus local cultural realities. Ultimately, this study contributes a comprehensive synthesis that underscores the necessity of interdisciplinary collaboration and reflexive governance in the pursuit of fair and trustworthy machine learning systems, while outlining future research directions aimed at bridging theory, policy, and practice.

A Pathomorphological Algarithm For Changes in Internal Organs in Suddenly Diets Under 35 With A Hereditary Prediction

Kurbanov Ravshanbek Davletovich — 2026-02-24

This article presents a scientifically based pathomorphological algorithm for examining internal organs in individuals who died suddenly under 35 years of age with a known or suspected hereditary predisposition to fatal conditions.

Impact Of Type 2 Diabetes Mellitus On Outcomes Of Coronary Artery Bypass Grafting In Patients With Coronary Artery Disease: A Retrospective Analysis

D.A. Mamaradzhapova — 2026-02-12

Background: The issue of coronary artery disease (CAD) is particularly significant among patients with type 2 diabetes mellitus (T2DM), the prevalence of which is steadily increasing globally. While coronary artery bypass grafting (CABG) is proven effective, the presence of T2DM significantly affects perioperative risks and long-term outcomes of the procedure.

Objective: To conduct a comparative analysis of demographic, clinical, surgical parameters, and postoperative complications in patients with CAD depending on the presence or absence of T2DM.

Materials and Methods: Data from 384 patients who underwent elective CABG were analyzed. Patients were divided into two groups: 125 patients with T2DM (Group 1) and 259 patients without diabetes (Group 2). Data analysis was performed using nonparametric methods in SPSS 26.0 and R 4.0.2, with statistical significance set at p ≤ 0.05.

Results: A higher proportion of women (30.4%) and pronounced comorbidity were observed in patients with T2DM. The incidence of acute myocardial infarction (AMI) and effort angina was comparable in both groups, but postinfarction cardiosclerosis (PICS) and chronic heart failure (CHF) were more prevalent in patients with T2DM. Early postoperative complications (arrhythmias, acute cardiovascular insufficiency, stroke) were statistically significantly more frequent in patients with T2DM, while hospital mortality did not differ: 4.8% in patients with T2DM and 3.8% in those without diabetes. Surgical characteristics, including the use of cardiopulmonary bypass (CPB) and the number of grafts, showed minimal differences between groups, indicating a standardized approach to CABG regardless of T2DM status.

Conclusions: The presence of T2DM in patients with CAD significantly affects the frequency of early postoperative complications but does not impact hospital mortality after CABG, suggesting an increased risk of adverse outcomes.

Applications: To develop strategies for optimizing the treatment of patients with T2DM undergoing CABG, considering their elevated risk of complications.

Clinical And Pathophysiological Aspects Of Liver Cirrhosis

Niyozova Yorqinoy Mirzaxamdamovna — 2026-02-16

Diffuse fibrosis, nodule development, and loss of the hepatic parenchyma are the hallmarks of cirrhosis of the liver (CP), a chronic progressive illness that causes portal hypertension and hepatic failure. The illness is linked to a high rate of morbidity and death globally and is the last stage of many chronic liver illnesses. The origin, pathophysiology, clinical signs, diagnostic methods, therapeutic modalities, and prognosis of liver cirrhosis are all thoroughly covered in this article. The significance of early diagnosis and multidisciplinary care is emphasized in order to avoid consequences such hepatocellular cancer, ascites, variceal hemorrhage, and hepatic encephalopathy.