ViTBayesianNet: An adaptive deep bayesian network-aided alzheimer disease detection framework with vision transformer-based residual densenet for feature extraction using MRI images.

One of the most familiar types of disease is Alzheimer's disease (AD) and it mainly impacts people over the age limit of 60. AD causes irreversible brain damage in humans. It is difficult to recognize the various stages of AD, hence advanced deep learning methods are suggested for recognizing AD in its initial stages.

Prostate cancer prognosis using machine learning: A critical review of survival analysis methods.

Prostate Cancer is a disease that affects the male reproductive system. The irregularity of the symptoms makes it hard for the clinicians to pinpoint the disease in the earlier stages. Techniques such as Machine Learning, Data Science, Deep Learning, etc.

Comparative analysis of real-world data of frequent treatment sequences in metastatic prostate cancer.

Background: The incidence of prostate cancer is increasing worldwide. A significant proportion of patients develop metastatic disease and are initially prescribed androgen deprivation therapy (ADT). However, subsequent sequences of treatments in real-world settings that may improve overall survival remain an area of active investigation.

Optimizing wastewater treatment through artificial intelligence: recent advances and future prospects.

Artificial intelligence (AI) is increasingly being applied to wastewater treatment to enhance efficiency, improve processes, and optimize resource utilization. This review focuses on objectives, advantages, outputs, and major findings of various AI models in the three key aspects: the prediction of removal efficiency for both organic and inorganic pollutants, real-time monitoring of essential water quality parameters (such as pH, COD, BOD, turbidity, TDS, and conductivity), and fault detection in the processes and equipment integral to wastewater treatment. The prediction accuracy ( value) of AI technologies for pollutant removal has been reported to vary between 0.

Recent advances in the antioxidant activity of metal-curcumin complexes: a combined computational and experimental review.

Curcumin, an extensively studied phytochemical compound, has gained attention for its potential therapeutic applications across a spectrum of diseases. Its notable attributes include its relatively high tolerability within the human body and its perceived absence of adverse side effects. This review article presents a comprehensive overview of the antioxidant effects exhibited by complexes formed by curcumin and curcumin derived ligands with metals like Mn, Cu, Fe, Zn, Ga and In, which leads to toxic effects beyond a certain limit, based on both experimental and theoretical findings.

The nexus between remittances, natural resources, technological innovation, economic growth, and environmental sustainability in Pakistan.

Globally, the issues about sustainable development are on the increase. Moreover, these issues are rising every day in Pakistan, as remittances are increasing, technology innovation is ambiguous, natural resources are degraded, and economic expansion might pose serious challenges to the environment. Thus, this research looks at how remittances, natural resources, technological innovation, and economic growth affect carbon dioxide (CO emissions in Pakistan by controlling energy consumption and urbanization from 1990 to 2019.

The Nexuses Between Social Media Marketing Activities and Consumers' Engagement Behaviour: A Two-Wave Time-Lagged Study.

This study examined how social media marketing activities (SMMA) influence consumers' engagement behaviour in developing countries. Based on the stimulus-organism-response theory, we examined the effect of SMMA on consumers' engagement intention and further investigated the moderating effect of social media sales intensity. The study employed a time-lagged design with two waves to confirm the hypothesised framework.

Stress Classification Using Brain Signals Based on LSTM Network.

The early diagnosis of stress symptoms is essential for preventing various mental disorder such as depression. Electroencephalography (EEG) signals are frequently employed in stress detection research and are both inexpensive and noninvasive modality. This paper proposes a stress classification system by utilizing an EEG signal.

E-Commerce and Consumer Protection in India: The Emerging Trend.

Given the rapid growth and emerging trend of e-commerce have changed consumer preferences to buy online, this study analyzes the current Indian legal framework that protects online consumers interests. A thorough analysis of the two newly enacted laws, i.e.

Working in lockdown: the relationship between COVID-19 induced work stressors, job performance, distress, and life satisfaction.

Background & Aim: In the wake of COVID-19, organizations all over India have closed their premises and shifted to work from home policy to curb the further spread of the virus. This has led to increased stress and anxiety among employees, which explicably affects their satisfaction with life. Thus, the present study analyses the effect of COVID-19 induced stressors (role overload, lifestyle choices, family distraction, and occupational discomfort) on employees' distress levels and job performance.