Telemedicine was introduced on connected IoT-based resource networking infrastructure. With technological evolution and artificial intelligence, the framework has expanded grips beyond connecting remote patients. Augmented intelligence (AuI) adds value to current telemedicine by coordinating with management pools of IoT devices communication channels provide a reliable enterprise ecosystem smart cities. In this article, novel approach for recommendation in via AuI is proposed. The acquires...

Social media plays a pivotal role in the daily activities of individuals, serving as medium for dissemination events, activities, and information through various forms posts, including tweets, status updates, pictures. The source is determined by analyzing impact user's association with particular tweet. In this research paper, we present framework based on principles Federated Learning (FL) to classify analyze tweets across different social platforms. incorporates feature mapping indexing...

The autonomous connected ambulance (ACA) has been an unprecedented necessity in the demand–supply management sector of healthcare sector. However, traditional prototypes designed for such unmanned vehicle do not match demands advanced communication technologies incorporated today's sophisticated distributed networks. As a result, current era edge computing strengthened by many AI-enabled algorithms, there is urgent need to design route resource recommendation (R3) protocol ACA under Edge-AI....

Over the past decade, there has been a significant surge in consumer application services and server connectivity, this trend is expected to double 2030. The primary contributors increased demand for network resources are devices connected through third-party service providers mobile operators. Many prominent rely on client-server architecture, which can introduce latency delays communication channel. Additionally, peer-to-peer (P2P) places substantial load eHealth servers, leading delays....

Mobiles have become one of the most essential part our life with capabilities smart phone we can incorporate it a telemedicine terminology to monitor patient status remotely. The proposed system is mainly designed for rural Indian population suffering from hypertension and Hypotension also programmed capture pre-cardiac arrest situation remote people take precautions in contacting medical/Healthcare Unit assistance. Biomedical sensors photo-electronic are used input characteristics...

Telemedicine in India is expanding and thus it essential for application to reduce storage transmission bandwidth. The prime objective this paper demonstrate an investigative protocol medical image compression telemedicine. method based on Integer Wavelet Transform (IWT) Huffman's Coding with added novelty of machine learning terminology extracting the region pixel density optimized layering neighboring ratio analysis. experimental results are evaluated demonstrated open datasets has...

Biomedical image processing and decision making is a growing research demand under global pandemic situation. The quality of medical images plays vital role in streamlining remote diagnosis via telemedicine platform, providing unambiguous results supports. This paper presents an improved Medical Image Content Quality (MICQ) technique it aims to enrich the Magnetic Resonance (MR) content or pixels based on semi supervised clustering for process deeper analysis investigation identify normal...

Hospitals serve as critical hubs for global healthcare, offering essential medical services. However, a pressing issue is the lack of 24/7 facilities in rural areas, particularly during overnight hours. To bridge this gap, we propose Robotic Medical Support ChatBot (RMSCB) system. This innovative online platform leverages machine learning to autonomously predict diagnoses and provide temporary solutions, accessible at any time. The RMSCB system comprises three key stages: pre-processing,...

Privacy in medical records while data sharing is a major concern for distributed learning models. The dataset generated and shared via Electronic Medical Records (EMR) consist of sensitive information such as patient identify experts recommendations, causes setbacks training larger models, augmentation polluting datasets with recursive attributes. processing de-identification proposed this article to preserve enhance the privacy EMR. technique termed PrEGAN (i.e.) Enhanced Generative...

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 global population has been diagnosed with PD, this figure expected double 2040. Early accurate diagnosis critical slowing down progression disease reducing long-term disability. Due complexity disease, it difficult accurately diagnose using traditional clinical tests. Therefore, become...

Abstract Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm standard Internet (IoT) and (IoMT) devices, particularly at server computational layers, poses a formidable challenge. In this paper, we present novel methodology for categorizing AIoMT through application decentralized processing, referred to as "Federated Learning" (FL). Our approach involves deploying system on IoT labeled IoMT training purposes attribute extraction. Through process, extract...

Telemedicine is venturing towards development, resulting in larger data evaluation online. Medical signals are major Para-types telemedicine transmission channel line. Since, biomedical sensitive and acute nature, a smallest ratio of hampering causes false positive prediction on resultant diagnosis. In this paper, machine learning algorithm discussed to regenerate the under transmission. The decomposed four layer DWT prior achieve signal optimization through channel. methodology uses...

In last decade, temporal medical data analysis is considered as core samples in technological processing and research. However, a practical scenario of unachieved. this paper, the authors have projected diagnosis real time heart signals under motifs features over Electro Cardio Graphic (ECG) Phono (PCG) datasets. A combination local motif patters for ECG datasets Featured signal PCG dataset with feed machine learning techniques appended. case study performed on digital Electrocardiogram...

This paper presents, a new approach of Medical Image Pixels Clustering (MIPC), aims to trace the dissimilar patterns over Magnetic Resonance (MR) image through process automatically identify appropriate number distinct clusters based on different improved unsupervised clustering schemes for enrichment, pattern predication and deeper investigation. The proposed MIPC consists two stages: validation. In stage, identifies gray scale MR three likely Limited Agglomerative (iLIAC), Dynamic...