As healthcare systems around the world face challenges such as escalating costs, limited access, and growing demand for personalized care, artificial intelligence (AI) is emerging as a key force for transformation. This review is motivated by the urg...
The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on...
Medical image segmentation plays a critical role in accurate diagnosis and treatment planning, enabling precise analysis across a wide range of clinical tasks. This review begins by offering a comprehensive overview of traditional segmentation techni...
Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physician...
The current research is concerned with the synthesis of magnesium oxide (MgO) nanoparticles (NPs) from Abrus precatorius L. bark extract via the green chemistry method. The synthesized MgO NPs was confirmed by using several characterization methods l...
Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consis...
Medical digital twins, which represent medical assets, play a crucial role in connecting the physical world to the metaverse, enabling patients to access virtual medical services and experience immersive interactions with the real world. One serious...
Nano-oncology is a branch of biomedical research and engineering that focuses on using nanotechnology in cancer diagnosis and treatment. Nanomaterials are extensively employed in the field of oncology because of their minute size and ultra-specificit...
Bioceramics, with excellent bioactivity and biocompatibility, have been widely used in dentistry, particularly in endodontics. Mineral trioxide aggregate (MTA) is the most widely used bioceramic in endodontics. Recently, many new bioceramics have bee...
Chlorella sp. and Spirulina (Arthrospira) sp. account for over 90% of the global microalgal biomass production and represent one of the most promising aquiculture bioeconomy systems. These microorganisms have been widely recognized for their nutritio...
In the twenty-first century, nanotechnology has emerged as a potentially game-changing innovation. Essential minerals are mostly unavailable in modern cropping systems without the application of synthetic fertilizers, which have a serious negative im...
Advancements in biological wastewater treatment with sustainable and circularity approaches have a wide scope of application. Biological wastewater treatment is widely used to remove/recover organic pollutants and nutrients from a diverse wastewater...
The opacity of deep learning makes its application challenging in the medical field. Therefore, there is a need to enable explainable artificial intelligence (XAI) in the medical field to ensure that models and their results can be explained in a man...
The demineralization process conditions the structure of the enamel and begins with a superficial decalcification procedure that makes the enamel surface porous and gives it a chalky appearance. White spot lesions (WSLs) are the first clinical sign t...
Early diagnosis and classification of arrhythmia from an electrocardiogram (ECG) plays a significant role in smart healthcare systems for the health monitoring of individuals with cardiovascular diseases. Unfortunately, the nonlinearity and low ampli...
In the clinical and healthcare domains, medical images play a critical role. A mature medical visual question answering system (VQA) can improve diagnosis by answering clinical questions presented with a medical image. Despite its enormous potential...
Recently, various methods have been developed to identify COVID-19 cases, such as PCR testing and non-contact procedures such as chest X-rays and computed tomography (CT) scans. Deep learning (DL) and artificial intelligence (AI) are critical tools f...
Silver nanoparticles have been a recent focus of many researchers in dentistry, and their potential uses and benefits have drawn attention in dentistry and medicine. The fabrication and utilization of nanoscale substances and structures are at the co...
Biosynthesized nano-composites, such as silver nanoparticles (AgNPs), can be engineered to function as smart nano-biomedicine platforms for the detection and management of diverse ailments, such as infectious diseases and cancer. This study determine...
This review examines the increasing application of artificial intelligence (AI) and/or machine learning (ML) in microalgae processes, focusing on their ability to improve production efficiency, yield, and process control. AI/ML technologies are used...
Global pollution from fossil plastics is one of the top environmental threats of our time. At their end-of-life phase, fossil plastics, through recycling, incineration, and disposal result in microplastic formation, elevated atmospheric CO2 levels, a...
This study evaluates the reproducibility of machine learning models that integrate radiomics and deep features (features extracted from a 3D autoencoder neural network) to classify various brain hemorrhages effectively. Using a dataset of 720 patient...
The golden rule in tissue engineering is the creation of a synthetic device that simulates the native tissue, thus leading to the proper restoration of its anatomical and functional integrity, avoiding the limitations related to approaches based on a...
The utilization of lasers has been regarded as a novel technique for the purposes of clinical use in the dental field. Recently, numerous studies have been conducted on the potential applications of laser therapy in endodontics. Moreover, due to thei...
Alzheimer’s disease (AD) is a progressive neurological problem that causes brain atrophy and affects the memory and thinking skills of an individual. Accurate detection of AD has been a challenging research topic for a long time in the area of...
Cardiovascular diseases are the leading cause of morbidity and mortality in the United States. Cardiac tissue engineering is a direction in regenerative medicine that aims to repair various heart defects with the long-term goal of artificially rebuil...
Lung and colon cancer are among humanity’s most common and deadly cancers. In 2020, there were 4.19 million people diagnosed with lung and colon cancer, and more than 2.7 million died worldwide. Some people develop lung and colon cancer simulta...
Recently, deep learning and the Internet of Things (IoT) have been widely used in the healthcare monitoring system for decision making. Disease prediction is one of the emerging applications in current practices. In the method described in this paper...
Immobilization using external or internal splints is a standard and effective procedure to treat minor skeletal fractures. In the case of major skeletal defects caused by extreme trauma, infectious diseases or tumors, the surgical implantation of a b...
Caesarean section (CS) rate has seen a significant increase in recent years, especially in industrialized countries. There are, in fact, several causes that justify a CS; however, evidence is emerging that non-obstetric factors may contribute to the...
This review article explores the use of Virtual Reality (VR) technology in cognitive rehabilitation for individuals with neurological conditions, such as stroke, traumatic brain injury, and neurodegenerative diseases. The introduction highlights the...
The global development of technologies now enters areas related to human health, with a transition from conventional to personalized medicine that is based to a significant extent on (bio)printing. The goal of this article is to review some of the pu...
Cardiac magnetic resonance (CMR) is an essential clinical tool for the assessment of cardiovascular disease. Deep learning (DL) has recently revolutionized the field through image reconstruction techniques that allow unprecedented data undersampling...
In the advancement of medical image super-resolution (SR), the Deep Residual Feature Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This work presents DRFDCAN, a model that innovates traditional SR approaches by in...
The concept of extraction socket healing has been severally researched and reported over the years, since tooth extraction remains one of the most common procedures performed in the dental clinic. Understanding this healing process is of utmost impor...
A low-cost, fast, dependable, repeatable, non-invasive, portable, and simple-to-use vascular screening tool for coronary artery diseases (CADs) is preferred. Photoplethysmography (PPG), a low-cost optical pulse wave technology, is one method with thi...
The advancement achieved in Tissue Engineering is based on a careful and in-depth study of cell–tissue interactions. The choice of a specific biomaterial in Tissue Engineering is fundamental, as it represents an interface for adherent cells in...
The emergence of digital dentistry has led to the introduction of various three-dimensional (3D) printing materials in the market, specifically for provisional fixed restoration. This study aimed to undertake a systematic review of the published lite...
Motor impairment has a profound impact on a significant number of individuals, leading to a substantial demand for rehabilitation services. Through brain–computer interfaces (BCIs), people with severe motor disabilities could have improved comm...
Background: Since the onset of the COVID-19 pandemic in early 2020, the importance of timely and effective assessment of mental well-being has increased dramatically. Machine learning (ML) algorithms and artificial intelligence (AI) techniques can be...
One of the most promising research initiatives in the healthcare field is focused on the rising incidence of skin cancer worldwide and improving early discovery methods for the disease. The most significant factor in the fatalities caused by skin can...
Dental X-ray images are important and useful for dentists to diagnose dental diseases. Utilizing deep learning in dental X-ray images can help dentists quickly and accurately identify common dental diseases such as periodontitis and dental caries. Th...
In recent years, the development of adaptive models to tailor instructional content to learners by measuring their cognitive load has become a topic of active research. Brain fog, also known as confusion, is a common cause of poor performance, and re...
This study proposes a new hybrid machine learning (ML) model for the early and accurate diagnosis of heart disease. The proposed model is a combination of two powerful ensemble ML models, namely ExtraTreeClassifier (ETC) and XGBoost (XGB), resulting...
This paper focuses on the use of local Explainable Artificial Intelligence (XAI) methods, particularly the Local Rule-Based Explanations (LORE) technique, within healthcare and medical settings. It emphasizes the critical role of interpretability and...
There is no doubt that brain tumors are one of the leading causes of death in the world. A biopsy is considered the most important procedure in cancer diagnosis, but it comes with drawbacks, including low sensitivity, risks during biopsy treatment, a...
Background: The accuracy of surgical guides is a relevant factor in both surgical safety and prosthetic implications. The impact of widespread fabrication technologies (milling and 3D printing) was investigated. Methods: Surgical guides manufactured...
Anomaly detection is a significant task in sensors’ signal processing since interpreting an abnormal signal can lead to making a high-risk decision in terms of sensors’ applications. Deep learning algorithms are effective tools for anomal...
Chronic wounds are associated with considerable patient morbidity and present a significant economic burden to the healthcare system. Often, chronic wounds are in a state of persistent inflammation and unable to progress to the next phase of wound he...
This paper presents an ensemble of pre-trained models for the accurate classification of endoscopic images associated with Gastrointestinal (GI) diseases and illnesses. In this paper, we propose a weighted average ensemble model called GIT-NET to cla...
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