Dentistry and Medical Research

: 2021  |  Volume : 9  |  Issue : 1  |  Page : 1-

From the Editor

Karthikeyan Ramalingam 
 Department of Oral and Maxillofacial Pathology and Oral Microbiology, Surendera Dental College and Research Institute, Sri Ganganagar, Rajasthan, India

Correspondence Address:
Karthikeyan Ramalingam
Department of Oral and Maxillofacial Pathology and Oral Microbiology, Surendera Dental College and Research Institute, Sri Ganganagar, Rajasthan

How to cite this article:
Ramalingam K. From the Editor.Dent Med Res 2021;9:1-1

How to cite this URL:
Ramalingam K. From the Editor. Dent Med Res [serial online] 2021 [cited 2021 Dec 2 ];9:1-1
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Digitalization of histopathological slides, also called as whole slide imaging (WSI), performed with a digital scanner for image visualization. The United States Food and Drug Administration has approved this system for the diagnosis of primary surgical pathology. This led to automated image analysis with artificial intelligence-derived algorithms, advances in diagnostic pathology, applications in telepathology with easy internet access, avoiding the need of physical storage, and risk of slide breakage or loss of staining, etc. Deep learning with convolutional neural networks can help in the automatic classification of malignancies using digital pathology images. It can also be used for pathology training, teleconferencing, tumor boards, tissue banking, biomarker development, virtual immunohistochemistry, automated smear, and blood film analysis, digital archival of cases, human genome project, and computer-assisted screening techniques. The BestCyte Cell Sorter uses automated WSI to generate high-resolution digitized slides that are analyzed with image algorithms to detect and group abnormal cells. Radiologic imaging, proteomics, and genomics-based measurements could be combined with digital pathology to predict the disease aggression, prognosis, and estimate patient outcome. In the near future, slide scanners can share the current role of microscopes in the practice of pathology leading to more accurate and rapid diagnosis.

Medical informatics deals with the science of how to use the data, information, and knowledge to improve human health and delivery of health-care services. Clinical informatics deals with the information management in health care to promote safe, efficient, effective, personalized, and responsive care. Pathology informatics (PI) involves the collection, examination, and storage of large data sets derived from clinical/pathology/research laboratories to advance patient care and enhance the information related to diseases. It can be applied at the individual, institutional, community, and population levels. PI Essentials for Residents educate the pathology residents about the important knowledge and skills related to PI. System for Informatics in the Molecular Pathology Laboratory (SIMPL) is a free and open-source laboratory information management system to handle all the stages of next-generation sequencing (NGS) from the test order to reporting. PI deals with information technology in the laboratory, its impact on the workflow process, and staff interaction with these tools. Precision medicine is based on PI to assist with remote specimen triage using telecytology with real-time robotic microscopy, NGS, data mining, laboratory information system, electronic medical records (EMRs), and digital imaging. There are only few systems that can handle both wet bench (nucleic acid extraction and sequencing) and dry bench (data pipeline analysis) in a molecular laboratory. Downstream informatics has to generate the readable reports to be stored in EMR.