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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.
  • 471
  • 22 Nov 2021
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.
  • 469
  • 18 Jan 2023
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.).
  • 442
  • 15 Feb 2022
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.
  • 438
  • 30 Sep 2021
Topic Review
Automated Dose Dispensed Medicine in Home Care
Automated dose dispensing (ADD) systems are today used around the world but little is known about how patients react to  receiving the daily doses of medicine from a machine rather than from a human. This entry reveals a general satisfaction towards ADD robots as an intervention.
  • 436
  • 06 Dec 2021
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.
  • 426
  • 26 May 2021
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. 
  • 424
  • 05 Jul 2021
Topic Review Peer Reviewed
Telemental Health and Diverse Populations amid COVID-19
Telemental health is defined as the delivery of psychological and mental health services via telecommunication technologies, including telephone-delivered therapy, videoconferencing, and internet-delivered programs. Research indicates that telemental health services are as effective as in-person services, and a dramatic increase in the use of telemental health has been observed during COVID-19. However, there are still persistent challenges and concerns about mental health providers’ competencies, clients’ data privacy, and legal and regulatory issues during this pandemic. Additionally, disparities in the use of telemental health services with diverse populations, based on factors such as age, gender, ethnicity, socioeconomic status, language, and culture, have been identified during this pandemic.
  • 419
  • 29 Mar 2023
Topic Review
Biocatalytic Syntheses of Antiplatelet Metabolites
Antithrombotic thienopyridines, such as clopidogrel and prasugrel, are prodrugs that undergo a metabolic two-step bioactivation for their pharmacological efficacy. In the first step, a thiolactone is formed, which is then converted by cytochrome P450-dependent oxidation via sulfenic acids to the active thiol metabolites. These metabolites are the active compounds that inhibit the platelet P2Y12 receptor and thereby prevent atherothrombotic events. 
  • 418
  • 27 Oct 2021
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.
  • 411
  • 10 Jan 2022
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