Inmaculada Tomás Carmona

I have been a University Professor of Stomatology in the Department of Surgery and Medical-Surgical Specialties at the University of Santiago de Compostela (USC) since 2022. Between 2011 and 2014, I was a member of the Dean's Team of the Faculty of Medicine and Dentistry, as Vice-Dean of Dentistry. Currently, I am Coordinator of the Clinical and Research Unit in Dentistry for Patients with Special Needs, Coordinator of the Research Group "Oral Sciences Research Group" of the USC, belonging to the Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS). I am a Collaborating Researcher in international institutions such as the Eastman Dental Institute, Queen Mary University of London and King's College London.

I am Associate Editor of several high impact JCR scientific journals. I have received numerous research awards from international and national scientific societies such as IADR, SEPA, SEOC and SEOII, as well as from public and private institutions. I am the inventor of three nationally registered patents. I have three six-year research periods recognised by the CNEAI, an H index= 43 and a number of references= 4800 (Google Scholar, as of 8 January 2023).

I have participated in 25 national (funded by the Instituto de Salud Carlos III) and regional competitive R&D&I projects, as well as in contracts with international companies in the biomedical sector such as Johnson and Johnson and Lacer. In 15 of these activities I am Principal Investigator, of which 8 are competitive projects and 7 are contracts with companies.

I have participated in the elaboration of more than 110 publications in journals with impact index, more than 25 book chapters and directed 17 PhD Theses (8 of which received the Extraordinary PhD Award in Health Sciences, USC).

My research is focused on the scientific advancement of dental sciences, starting initially in the field of oral microbiology to incorporate in the last ten years, omic technologies and artificial intelligence techniques. The research group that I lead, Oral Sciences Research Group at USC and FIDIS, is currently focused on the development of two lines of research: 1) Understanding and diagnosis of human oral diseases through the application and development of bioinformatics techniques in omic technologies; 2) Dental diagnosis on images of the oral cavity through the application and development of artificial intelligence techniques.

Regarding the first line of research, we were the first group in our country to carry out the bioinformatics characterisation of the oral microbiome associated with periodontitis and periodontal health. From a methodological point of view, we have performed several in silico analyses to determine the coverage of the primer pairs used in the sequencing of the oral microbiome, detecting the presence of matched amplicons and amplicons with ≥97% similarity values (OTUs). To carry out these objectives, we developed the PrimerEvalPy software, a tool that allows in silico primer analysis prior to any sequencing process, thus contributing to improve the quality and reliability of microbial diversity results of any polymicrobial ecosystem. In order to evaluate the predictive capacity of the oral microbiome as a diagnostic tool in the era of personalised medicine, we have developed a taxonomic classifier, called MicroMeta Evaluator, based on machine learning techniques that allows us to improve the classification rate of current methods for sequences with sequencing errors, and to obtain the definition of a given oral clinical condition. We are currently analysing the oral proteome using machine learning techniques for the detection and identification of new diagnostic molecular biomarkers, evaluating their relationship with the oral microbiome.

Regarding the second line of research, with the aim of providing automated diagnosis of chronological age and sex on radiological images, we have developed Dentius Age, a software based on high-precision deep neural networks that can work with the entire image, selecting exclusively the mandible or exclusively the mandibular teeth. In order to automatically quantify the levels of dental plaque, we developed the software Dentius Deep Plaque and Dentius Biofilm, establishing the first automated protocol for plaque analysis, both macroscopically and microscopically, which allows in situ evaluation of the patterns of evolution in different clinical conditions, as well as the efficacy of different oral hygiene measures.