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Topic Review
Computer-Aided Breast Cancer Diagnosis
A computer-aided diagnosis (CAD) expert system is a powerful tool to efficiently assist a pathologist in achieving an early diagnosis of breast cancer. This process identifies the presence of cancer in breast tissue samples and the distinct type of cancer stages. In a standard CAD system, the main process involves image pre-processing, segmentation, feature extraction, feature selection, classification, and performance evaluation. Breast cancer can be distinguished as benign (non-cancerous) and malignant (cancerous/metastatic) tumours. Benign tissue refers to changes in normal tissue of breast parenchyma, which does not relate to the development of malignancy . Contrarily, malignant tissue can be categorised into two types: in-situ carcinoma and invasive carcinoma.  
  • 1.1K
  • 15 Jun 2021
Topic Review
Artificial Intelligence and Machine Learning in Stroke Care
Stroke is an emergency for which delays in treatment can lead to significant loss of neurological function and be fatal. Technologies that increase the speed and accuracy of stroke diagnosis or assist in post-stroke rehabilitation can improve patient outcomes. No resource exists that comprehensively assesses artificial intelligence/machine learning (AI/ML)-enabled technologies indicated for the management of ischemic and hemorrhagic stroke.
  • 1.1K
  • 16 Jun 2023
Topic Review
Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care
Primary care stands as a cornerstone in healthcare, serving as the first point of contact and managing the most significant number of patients in the United States and worldwide. AI can mimic human reasoning and behavior and handle the increasing volume of medical data within healthcare systems. Machine learning (ML) is the most common AI technique used.
  • 1.1K
  • 27 Mar 2024
Topic Review
Methods for Supervised Learning in Diagnosis of COVID-19
The methods for supervised learning in diagnosis of COVID-19 refer to the samples used for model training being labeled. The label information is fully utilized to guide network model training. The advantage is that the model accuracy can be effectively improved by learning a large amount of label information and the model is easy to evaluate. The current state of deep learning for COVID-19 classification and segmentation tasks from aspects of supervised learning is summarized, including summarizing the application of VGG, ResNet, DenseNet and lightweight networks to the classification task of COVID-19, and summarizing the application of the attention mechanism, multiscale mechanism, residual connectivity mechanism, and dense connectivity mechanism to the segmentation task of COVID-19.
  • 1.1K
  • 22 Mar 2023
Topic Review
Current Landscape of Sonodynamic Therapy for Treating Cancer
Recently, ultrasound has advanced in its treatment opportunities. One example is sonodynamic therapy, a minimally invasive anti-cancer therapy involving a chemical sonosensitizer and focused ultrasound. The combination of the ultrasound and chemical sonosensitizer amplifies the drug’s ability to target cancer cells. Combining multiple chemical sonosensitizers with ultrasound can create a synergistic effect that could effectively disrupt tumorigenic growth, induce cell death, and elicit an immune response. 
  • 1.1K
  • 15 Dec 2021
Topic Review
Treat COVID-19 through Mass Spectrometry and Next-Generation Sequencing
COVID-19 is caused by a coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The difficulty in containing SARS-CoV-2 has underscored the need for techniques such as mass spectrometry in the diagnosis and treatment of COVID-19. Mass spectrometry-based methods have been employed in several studies to detect changes in interactions among host proteins, and between host and viral proteins in COVID-19 patients. The methods have also been used to characterize host and viral proteins, and analyze lipid metabolism in COVID-19 patients. Information obtained using the above methods are complemented by high-throughput analysis of transcriptomic and epigenomic changes associated with COVID-19, coupled with next-generation sequencing.
  • 1.1K
  • 22 Nov 2021
Topic Review
AI in Thyroid Cancer Diagnosis
Artificial intelligence (AI) exceptional capabilities, including pattern recognition, predictive analytics, and decision-making skills, enable the development of systems that can analyze complex medical data at a scale and precision beyond human capacity. AI has significantly impacted thyroid cancer diagnosis, offering advanced tools and methodologies that promise to revolutionize patient outcomes.
  • 1.1K
  • 01 Nov 2023
Topic Review
Deep Learning Models for Radiography in Chest Disease
Chest X-ray radiography (CXR) is among the most frequently used medical imaging modalities. It has a preeminent value in the detection of multiple life-threatening diseases. Radiologists can visually inspect CXR images for the presence of diseases. Most thoracic diseases have very similar patterns, which makes diagnosis prone to human error and leads to misdiagnosis. Machine learning (ML) and deep learning (DL) provided techniques to make this task more efficient and faster. Numerous experiments in the diagnosis of various diseases proved the potential of these techniques.
  • 1.1K
  • 18 Jan 2023
Topic Review
NER&RE Techniques on Clinical Texts
Out of the various text mining tasks and techniques, our goal in this paper is to review the current state-of-the-art in Clinical Named Entity Recognition (NER) and Relationship Extraction (RE)-based techniques. Clinical NER is a natural language processing (NLP) method used for extracting important medical concepts and events i.e., clinical NEs from the data. Relationship Extraction (RE) is used for detecting and classifying the annotated semantic relationships between the recognized entities.
  • 1.0K
  • 30 Sep 2021
Topic Review
De Novo Design of HIV-1 Protease Inhibitors
Acquired immunodeficiency syndrome (AIDS) caused by the human immunodeficiency virus (HIV) continues to be a public health problem. In 2020, 680,000 people died from HIV-related causes, and 1.5 million people were infected. Antiretrovirals are a way to control HIV infection but not to cure AIDS.
  • 1.0K
  • 17 Dec 2021
Topic Review
Feedback and Pharmacy Education
Feedback is an effective pedagogy aimed to create cognitive dissonance and reinforce learning as a key component of clinical training programs. Pharmacy learners receive constant feedback. However, there is limited understanding of how feedback is utilized in pharmacy education.
  • 935
  • 19 May 2021
Topic Review
Machine Learning and Eye Movements
Humans are a vision-dominated species; what we perceive depends on where we look. Therefore, eye movements (EMs) are essential to our interactions with the environment, and experimental findings show EMs are affected in neurodegenerative disorders (ND). This could be a reason for some cognitive and movement disorders in ND. Therefore, several research aim to establish whether changes in EM-evoked responses can tell us about the progression of ND, such as Alzheimer’s (AD) and Parkinson’s diseases (PD), in different stages.
  • 929
  • 22 Feb 2023
Biography
Radha Ambalavanan
Proficient in utilizing comprehensive academic databases such as PubMed, ScienceDirect, Scopus, and Web of Science. Over 14 years of experience in medical literature databases and research methods. Proficient in PRISMA guidelines for ethical biomedical research. Expertise in writing and formatting papers for academic journals. Familiarity with citation styles: Chicago Manual of Style 17th Ed
  • 918
  • 24 Nov 2025
Topic Review
Prediction of Cell-Line Drug Sensitivity Using Network-Based Methods
The development of reliable predictive models for individual cancer cell lines to identify an optimal cancer drug is a crucial step to accelerate personalized medicine, but vast differences in cancer cell lines and drug characteristics make it quite challenging to develop predictive models that result in high predictive power and explain the similarity of cell lines or drugs.
  • 915
  • 11 Mar 2022
Topic Review
Routine Laboratory Biomarkers Detecting COVID-19
No routine laboratory biomarkers perform well enough in diagnosing COVID-19 in isolation for them to be used as a standalone.
  • 904
  • 26 May 2021
Topic Review
Methods for Imaging and Evaluation of Scoliosis
Scoliosis is defined as a three-dimensional spinal deformity consisting of a lateral curvature greater than 10 degrees with rotation of the vertebrae within the curve. It can be identified as congenital, neuromuscular or idiopathic. Idiopathic scoliosis (IS) can be further classified by age of onset: infantile (birth to two years), juvenile (three to nine years), and adolescent (10 years and older). It is the most common pediatric musculoskeletal disorder that causes a three-dimensional (3D) spinal deformity. The deformity is always 3D because it also involves an axial rotation of the vertebrae, not just displacement and rotation in the frontal plane. Adolescent IS is the most common form because the spinal deformity evolves during periods of significant physical growth. IS is diagnosed when other etiological factors cannot be identified, such as congenital neurological or musculoskeletal anomalies, or inflammatory or demyelinating processes leading to primary or secondary motor neuron damage (myotonia, myopathy, etc.).
  • 889
  • 15 Feb 2022
Topic Review
Public Perceptions around mHealth Applications
This study aimed to use Twitter to understand public perceptions around the use of six Saudi mHealth apps used during the COVID-19 pandemic: “Sehha”, “Mawid”, “Sehhaty”, “Tetamman”, “Tawakkalna”, and “Tabaud”. The specific objectives of this study are: (1) to examine the difference in communication network structure across the networks generated among the six mHealth apps included in our study; (2) to analyze the sentiment surrounding the six mHealth apps conversations; and (3) to evaluate the performance of a sentiment classifier using machine learning approaches.
  • 878
  • 10 Jan 2022
Topic Review
Immunological Features of Allergic Rhinitis
Inflammation of the upper respiratory tract in patients with allergic rhinitis (AR) may contribute to lower respiratory airways’ inflammation. T-helper 17 (Th17) cells and related cytokines are also involved in the immunological mechanism of AR along with the classical Th2 cells. It is hypothesized that upon Th2 pressure, the inflammatory response in the lungs may lead to Th17-induced neutrophilic inflammation. However, the findings for interleukin-17 (IL-17) are bidirectional. Furthermore, the role of Th17 cells and their counterpart—T regulatory cells—remains unclear in AR patients. It was also shown that a regulator of inflammation might be the individual circulating specific non-coding microRNAs (miRNAs), which were distinctively expressed in AR and bronchial asthma (BA) patients. 
  • 877
  • 08 Apr 2021
Topic Review
Apps in Anesthesia
Modern anesthesia continues to be impacted in new and unforeseen ways by digital technology. Combining portability and versatility, mobile applications or “apps” provide a multitude of ways to enhance anesthetic and peri-operative care.
  • 872
  • 30 Nov 2023
Topic Review
Prediction Models for Venous Thromboembolism
Venous thromboembolism (VTE) is a significant cause of mortality in patients with lung cancer. Despite the availability of a wide range of anticoagulants to help prevent thrombosis, thromboprophylaxis in ambulatory patients is a challenge due to its associated risk of haemorrhage. As a result, anticoagulation is only recommended in patients with a relatively high risk of VTE. Efforts have been made to develop predictive models for VTE risk assessment in cancer patients, but the availability of a reliable predictive model for ambulate patients with lung cancer is unclear. 
  • 871
  • 05 Jul 2021
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