Association of geographic tongue and fissured tongue with ABO blood group among adult psoriasis patients: a novel study from a tertiary care hospital in Saudi Arabia

Tongue feature dataset construction and real-time detection

BACKGROUND

Tongue diagnosis in traditional Chinese medicine (TCM) provides clinically important, objective evidence from direct observation of specific features that assist with diagnosis. However, the current interpretation of tongue features requires a significant amount of manpower and time. TCM physicians may have different interpretations of features displayed by the same tongue. An automated interpretation system that interprets tongue features would expedite the interpretation process and yield more consistent results.

MATERIALS AND METHODS

This study applied deep learning visualization to tongue diagnosis. After collecting tongue images and corresponding interpretation reports by TCM physicians in a single teaching hospital, various tongue features such as fissures, tooth marks, and different types of coatings were annotated manually with rectangles. These annotated data and images were used to train a deep learning object detection model. Upon completion of training, the position of each tongue feature was dynamically marked.

RESULTS

A large high-quality manually annotated tongue feature dataset was constructed and analyzed. A detection model was trained with average precision (AP) 47.67%, 58.94%, 71.25% and 59.78% for fissures, tooth marks, thick and yellow coatings, respectively. At over 40 frames per second on a NVIDIA GeForce GTX 1060, the model was capable of detecting tongue features from any viewpoint in real time.

CONCLUSIONS/SIGNIFICANCE

This study constructed a tongue feature dataset and trained a deep learning object detection model to locate tongue features in real time. The model provided interpretability and intuitiveness that are often lacking in general neural network models and implies good feasibility for clinical application.

Epidemiology of Psoriasis and Comorbid Diseases: A Narrative Review

Psoriasis is a chronic autoimmune inflammatory disease that remains active for a long period, even for life in most patients. The impact of psoriasis on health is not only limited to the skin, but also influences multiple systems of the body, even mental health. With the increasing of literature on the association between psoriasis and extracutaneous systems, a better understanding of psoriasis as an autoimmune disease with systemic inflammation is created. Except for cardiometabolic diseases, gastrointestinal diseases, chronic kidney diseases, malignancy, and infections that have received much attention, the association between psoriasis and more systemic diseases, including the skin system, reproductive system, and oral and ocular systems has also been revealed, and mental health diseases draw more attention not just because of the negative mental and mood influence caused by skin lesions, but a common immune-inflammatory mechanism identified of the two systemic diseases. This review summarizes the epidemiological evidence supporting the association between psoriasis and important and/or newly reported systemic diseases in the past 5 years, and may help to comprehensively recognize the comorbidity burden related to psoriasis, further to improve the management of people with psoriasis.