Spatio-Temporal Cluster Mapping System in Smart Beds for Patient Monitoring.

Innovative technological solutions are required to improve patients' quality of life and deliver suitable treatment. Healthcare workers may be able to watch patients from a distance using the Internet of Things (IoT) by using big data algorithms to analyze instrument outputs. Therefore, it is essential to gather information on use and health problems in order to improve the remedies.

Application of Deep Learning System Technology in Identification of Women's Breast Cancer.

: The classification of breast cancer is performed based on its histological subtypes using the degree of differentiation. However, there have been low levels of intra- and inter-observer agreement in the process. The use of convolutional neural networks (CNNs) in the field of radiology has shown potential in categorizing medical images, including the histological classification of malignant neoplasms.

Survival Analysis of Oncological Patients Using Machine Learning Method.

Currently, a considerable volume of information is collected and stored by large health institutions. These data come from medical records and hospital records, and the Hospital Cancer Registry is a database for integrating data from hospitals throughout Iraq. The data mining (DM) technique provides knowledge previously not visible in the database and can be used to predict trends or describe characteristics of the past.

Diagnosis of Breast Cancer Using Computational Intelligence Models and IoT Applications.

The use of computer-aided diagnostic (CAD) models has been proposed to aid in the detection and classification of breast cancer. In this work, we evaluated the performance of multilayer perceptron neural network and nonlinear support vector machine models to classify breast cancer nodules. From the contour of 569 samples, ten morphological features were used as input to the classifiers.

Processing Decision Tree Data Using Internet of Things (IoT) and Artificial Intelligence Technologies with Special Reference to Medical Application.

Alternative methods are available for a wide range of medical conditions. Idealistically, doctors would have a tool that would analyse their patients' symptoms and suggest the most accurate diagnosis and treatment plan. Artificial intelligence uses decision trees to predict and classify large datasets.

Diagnosing Cancer Using IOT and Machine Learning Methods.

Breast cancer affects one in every eight women and is the most common cancer. . To diagnose breast cancer, a potentially fatal condition, using microarray technology, large datasets can now be used.

Machine Learning of ZnO Interaction with Immunoglobulins and Blood Proteins in Medicine.

Toxoplasmosis is a zoonotic illness caused by . Those with a normal immune system normally recover without treatment. Immunocompromised individuals and pregnant women must be treated regularly.

Nursing Care Systematization with Case-Based Reasoning and Artificial Intelligence.

Of the most popular applications of artificial intelligence (AI), those used in the health sector are the ones that represent the largest proportion, in terms of use and expectation. An investigative systematization model is proposed in the scientific training of nursing professionals, by articulating epistemological positions from previous studies on the subject. In order to validate the model proposed, a prototype was created to present an application that could help nurses in their clinical processes, storing their experiences in a case base for future research.

Studying the Effects of Cold Plasma Phosphorus Using Physiological and Digital Image Processing Techniques.

The goal of this study is to see how cold plasma affects rabbit bone tissue infected with osteoporosis. The search is divided into three categories: control, infected, and treated. The rabbits were subjected to cold plasma for five minutes in a room with a microwave plasma voltage of "175 V" and a gas flow of "2.

Detection of Emotion of Speech for RAVDESS Audio Using Hybrid Convolution Neural Network.

Every human being has emotion for every item related to them. For every customer, their emotion can help the customer representative to understand their requirement. So, speech emotion recognition plays an important role in the interaction between humans.

Artificial Intelligence Technique of Synthesis and Characterizations for Measurement of Optical Particles in Medical Devices.

The aim of this study is to demonstrate the effect of particle size on semiconductor properties; artificial intelligence is being used for the research methods. As a result, we picked cadmium sulfide (CdS), which is a unique semiconductor material that is employed in a broad variety of current applications. Given that CdS has distinct electrical and optical characteristics, it may be employed in the production of solar cells, for example.

Approaches to Federated Computing for the Protection of Patient Privacy and Security Using Medical Applications.

Computing model may train on a distributed dataset using Medical Applications, which is a distributed computing technique. Instead of a centralised server, the model trains on device data. The server then utilizes this model to train a joint model.

A Survey Research on the Willingness of Gynecologists to Employ Mobile Health Applications.

In gynecological care, mHealth (mobile health) technology may play an important role. Medical professionals' willingness to use this technology is the key to its acceptance. Most doctors utilize mobile health technology; however, there is still room for improvement in the use of mHealth.

Advanced Deep Learning Human Herpes Virus 6 (HHV-6) Molecular Detection in Understanding Human Infertility.

To see if HHV-6 may be a cause of infertility, researchers looked at 18 men and 10 women who had unexplained critical fertility and had at least one prior pregnancy. HHV-6 DNA was discovered in both infertile and fertile peripheral blood mononuclear cells (PBMC) (12 and 14%, respectively); endometrial epithelial cells from 4/10 (40%) infertile women were positive for HHV-6 DNA; this viral DNA was not found in the endometrium of fertile women. When endometrial epithelial cells were cultivated, they produced viral early and late proteins, suggesting the existence of an infectious virus.

Machine Learning Implementation of a Diabetic Patient Monitoring System Using Interactive E-App.

Lifestyle influences morbidity and mortality rates in the world. Physical activity, a healthy weight, and a healthy diet are key preventative health behaviours that help reduce the risk of developing type 2 diabetes and its complications, such as cardiovascular disease. A healthy lifestyle has been shown to prevent or delay chronic diseases and their complications, but few people follow all recommended self-management behaviours.

E-Health System Characteristics, Medical Performance, and Healthcare Quality at Jordan's Health Centers.

This research explores how e-health systems' features (information quality, quality of the system, usability perceived, and perceived usefulness) contribute to improving medical personnel performance in medical centers, patient care, and physician-patient interactions in Jordan. The objective is to evaluate a single integrated model consisting of the technology acceptance model. This study used the logical research method and approach.

Machine Learning Algorithms for Prediction of Survival Curves in Breast Cancer Patients.

Today, cancer is the second leading cause of death worldwide, and the number of people diagnosed with the disease is expected to rise. Breast cancer is the most commonly diagnosed cancer in women, and it has one of the highest survival rates when treated properly. Because the effectiveness and, as a result, survival of the patient are dependent on each case, it is critical to know the modelling of their survival ahead of time.

The Dynamic Movement of Disaster Management Systems Based on Vehicle Networks and Applied on the Healthcare System.

In order to save human life and assets, the emergency management system (DMS) requires roving rescue teams to respond promptly and effectively. Installation and restoration of appropriate communication infrastructure are important for reducing the effect of disasters and enabling and coordinating information flow among relief teams working in the region. This paper describes a data collection system based on vehicular cloud network services that incorporates the advantages of both architectures of vehicular ad hoc networks (VANETs) with the cloud to establish vehicular cloud networks (VCNs).