Pneumonia is a microorganism infection that causes chronic inflammation of the human lung cells. Chest X-ray imaging most well-known screening approach used for detecting pneumonia in early stages. While chest-Xray images are mostly blurry with low illumination, strong feature extraction required promising identification performance. A new hybrid explainable deep learning framework proposed accurate disease using chest images. The workflow developed by fusing capabilities both ensemble...

Stress has become a dangerous health problem in our life, especially student education journey. Accordingly, previous methods have been conducted to detect mental stress based on biological and biochemical effects. Moreover, hormones, physiological effects, skin temperature extensively used for detection. However, the recent literature, biological, biochemical, physiological-based shown inconsistent findings, which are initiated due hormones' instability. Therefore, it is crucial study using...

Abstract Depression is a multifactorial disease with unknown etiology affecting globally. It’s the second most significant reason for infirmity in 2020, about 50 million people worldwide, 80% living developing nations. Recently, surge depression research has been witnessed, resulting multitude of emerging techniques developed prediction, evaluation, detection, classification, localization, and treatment. The main purpose this study to determine volume conducted on different aspects such as...

In the modern world, wearable smart devices are continuously used to monitor people’s health. This study aims develop an automatic mental stress detection system for researchers based on Electrocardiogram (ECG) signals from T-shirts using machine learning classifiers. We 20 subjects, including 10 (after twelve hours of continuous work in laboratory) and normal completing sleep or without any work). also applied three scoring techniques: Chalder Fatigue Scale (CFS), Specific (SFS),...

Abstract: Insomnia is well-known as trouble in sleeping and enormously influences human life due to the shortage of sleep. Reactive Oxygen Species (ROS) accrue neurons during waking state, sleep has a defensive role against oxidative damage dissipates ROS brain. In contrast, insomnia source inequity between generation removal by an endogenous antioxidant defense system. The relationship insomnia, depression, anxiety disorders damages cardiovascular systems' immune mechanisms functions....

According to research, classifiers and detectors are less accurate when images blurry, have low contrast, or other flaws which raise questions about the machine learning model’s ability recognize items effectively. The chest X-ray image has proven be preferred modality for medical imaging as it contains more information a patient. Its interpretation is quite difficult, nevertheless. goal of this research construct reliable deep-learning model capable producing high classification accuracy on...

Objective: This study aims to determine the efficacy of Acacia arabica (Lam.) Willd. and Cinnamomum camphora (L.) J. Presl. vaginal suppository in addressing heavy menstrual bleeding (HMB) their impact on participants' health-related quality life (HRQoL) analyzed using machine learning algorithms. Method: A total 62 participants were enrolled a double-dummy, single-center study. They randomly assigned either group (SG), receiving formulation prepared with gum ( Gond Babul ) camphor from...

Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine presently being studied with an eye of great curiosity hope. Hence, complementary alternative treatments for uncomplicated pelvic inflammatory disease (uPID) explored their efficacy. Therefore, this study determined the therapeutic efficacy safety Sesamum indicum Linn seeds Rosa damascena Mill Oil in uPID standard control. Additionally, we analyzed data...

We investigated the fusion of Intelligent Internet Medical Things (IIoMT) with depression management, aiming to autonomously identify, monitor, and offer accurate advice without direct professional intervention. Addressing pivotal questions regarding IIoMT’s role in identification, its correlation stress anxiety, impact machine learning (ML) deep (DL) on depressive disorders, challenges potential prospects integrating management IIoMT, this research offers significant contributions. It...

Bruxism is a sleep disorder in which the patient clinches and gnashes their teeth. detection using traditional methods time-consuming, cumbersome, expensive. Therefore, an automatic tool to detect this will alleviate doctor workload give valuable help patients. In paper, we targeted goal designed method bruxism from physiological signals novel hybrid classifier. We began with data collection. Then, performed analysis of estimation power spectral density. After that, classifier enable based...

Premenstrual syndrome (PMS) significantly lowers the quality of life and impairs personal social relationships in reproductive-age women. Some recommendations are that inappropriate oxidative stress inflammatory response involved PMS. Various nutritional supplements herbs showed neuro-psycho-pharmacological activity with antioxidant anti-inflammatory properties. This study aims to determine systematic review randomized controlled trials (RCTs) herbal medicine We also comprehensively...

Insomnia is a common sleep disorder in which patients cannot properly. Accurate detection of insomnia crucial step for disease analysis the early stages. The disruption getting quality one big sources cardiovascular syndromes such as blood pressure and stroke. traditional methods are time-consuming, cumbersome, more expensive because they demand long time from trained neurophysiologist, prone to human error, hence, accuracy diagnosis gets compromised. Therefore, automatic electrocardiogram...

A new artificial intelligence-based approach is proposed by developing a deep learning (DL) model for identifying the people who violate face mask protocol in public places. To achieve this goal, private dataset was created, including different images with and without masks. The trained to detect masks from real-time surveillance videos. detection (FMDNet) achieved promising of 99.0% terms accuracy violations (no mask) presented better capability compared other recent DL models such as...

A single-blind double-dummy randomized study was conducted in diagnosed patients (n = 66) to compare the efficacy of Linseeds (Linum usitatissimum L.), Psyllium (Plantago ovata Forssk.), and honey uncomplicated pelvic inflammatory disease (uPID) with standard drugs using experimental computational analysis. The pessary group received placebo capsules orally twice daily plus a per vaginum cotton powder from linseeds psyllium seeds, each weighing 3 gm, (5 mL) at bedtime. 100 mg doxycycline 400...

Abstract This comprehensive review article embarks on an extensive exploration of anxiety research, navigating a multifaceted landscape that incorporates various disciplines, such as molecular genetics, hormonal influences, implant science, regenerative engineering, and real‐time cardiac signal analysis, all while harnessing the transformative potential medical intelligence [medical + artificial (AI)]. By addressing fundamental research questions, this study investigated foundations...

Electrocardiography (ECG) is a well-known noninvasive technique in medical science that provides information about the heart's rhythm and current conditions. Automatic ECG arrhythmia diagnosis relieves doctors' workload improves effectiveness efficiency. This study proposes an automatic end-to-end 2D CNN (two-dimensional convolution neural networks) deep learning method with effective DenseNet model for addressing arrhythmias recognition. To begin, proposed trained evaluated on 97720 141404...

The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need use patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions are potentially fatal. Therefore, likely heart failure, precise PVC detection ECGs crucial. In clinical settings, cardiologists typically...

Accurate pre-harvest crop yield estimation is vital for agricultural sustainability and economic stability. The existing estimating models exhibit deficiencies in insufficient examination of hyperparameters, lack robustness, restricted transferability meta-models, uncertain generalizability when applied to data. This study presents a novel meta-knowledge-guided framework that leverages three diverse datasets explores meta-knowledge transfer frequent hyperparameter optimization scenarios....

Pandemic Patient Health Monitoring Platform (PPHMP) with the help of internet things (IoT) and cloud computing is proposed in this paper. As a result pandemic such as coronavirus outbreak, healthcare task needs system includes continuous diagnosis for monitoring patients supports decision making. The should be also helpful providers. Moreover, it accurate robust based on machine learning. PPHMP would terms its efficiency remote who are not supposed to visit hospital where health could...

Deep learning models have been successfully applied in a wide range of fields. The creation deep framework for analyzing high-performance sequence data piqued the research community’s interest. N4 acetylcytidine (ac4C) is post-transcriptional modification mRNA, an mRNA component that plays important role stability control and translation. ac4C method changes still not simple, time consuming, or cost effective conventional laboratory experiments. As result, we developed DL-ac4C, CNN-based...