A Novel Deep Learning-Based Black Fungus Disease Identification Using Modified Hybrid Learning Methodology.

Currently, countries across the world are suffering from a prominent viral infection called COVID-19. Most countries are still facing several issues due to this disease, which has resulted in several fatalities. The first COVID-19 wave caused devastation across the world owing to its virulence and led to a massive loss in human lives, impacting the country's economy drastically. A dangerous disease called mucormycosis was discovered worldwide during the second COVID-19 wave, in 2021, which lasted from April to July. The mucormycosis disease is commonly known as "black fungus," which belongs to the fungus family Mucorales. It is usually a rare disease, but the level of destruction caused by the disease is vast and unpredictable. This disease mainly targets people already suffering from other diseases and consuming heavy medication to counter the disease they are suffering from. This is because of the reduction in antibodies in the affected people. Therefore, the patient's body does not have the ability to act against fungus-oriented infections. This black fungus is more commonly identified in patients with coronavirus disease in certain country. The condition frequently manifests on skin, but it can also harm organs such as eyes and brain. This study intends to design a modified neural network logic for an artificial intelligence (AI) strategy with learning principles, called a hybrid learning-based neural network classifier (HLNNC). The proposed method is based on well-known techniques such as convolutional neural network (CNN) and support vector machine (SVM). This article discusses a dataset containing several eye photographs of patients with and without black fungus infection. These images were collected from the real-time records of people afflicted with COVID followed by the black fungus. This proposed HLNNC scheme identifies the black fungus disease based on the following image processing procedures: image acquisition, preprocessing, feature extraction, and classification; these procedures were performed considering the dataset training and testing principles with proper performance analysis. The results of the procedure are provided in a graphical format with the precise specification, and the efficacy of the proposed method is established.

Post coronavirus disease mucormycosis: a deadly addition to the pandemic spectrum.

OBJECTIVE: To study the possible association between invasive fungal sinusitis (mucormycosis) and coronavirus disease. METHODS: A prospective observational study was conducted at a tertiary care centre over four months, involving all patients with mucormycosis of the paranasal sinuses suffering from or having a history of coronavirus disease infection. RESULTS: Twenty-three patients presented with mucormycosis, all had an association with coronavirus disease 2019. The ethmoids (100 per cent) were the most common sinuses affected. Intra-orbital extension was seen in 43.47 per cent of cases, while intracranial extension was only seen in 8.69 per cent. Diabetes mellitus was present in 21 of 23 cases, and was uncontrolled in 12 cases. All patients had a history of steroid use during their coronavirus treatment. CONCLUSION: New manifestations of coronavirus disease 2019 are appearing over time. The association between coronavirus and mucormycosis of the paranasal sinuses must be given serious consideration. Uncontrolled diabetes and over-zealous use of steroids are two main factors aggravating the illness, and both of these must be properly checked.

A systematic review on SARS-CoV-2-associated fungal coinfections.

A severe pandemic of Coronavirus Disease (COVID-19) has been sweeping the globe since 2019, and this time, it did not stop, with frequent mutations transforming into virulent strains, for instance, B.1.1.7, B.1.351, and B.1.427. In recent months, a fungal infection, mucormycosis has emerged with more fatal responses and significantly increased mortality rate. To measure the severity and potential alternative approaches against black fungus coinfection in COVID-19 patients, PubMed, Google Scholar, World Health Organization (WHO) newsletters, and other online resources, based on the cases reported and retrospective observational analysis were searched from the years 2015-2021. The studies reporting mucormycosis with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) coinfection and/or demonstrating potential risk factors, such as a history of diabetes mellitus or suppressed immune system were included, and reports published in non-English language were excluded. More than 20 case reports and observational studies on black fungus coinfection in COVID-19 patients were eligible for inclusion. The results indicated that diabetes mellitus, hyperglycemic, and immunocompromised COVID-19 patients with mucormycosis were at a higher risk. We found that it was prudent to assess the potential risk factors and severity of invasive mycosis via standardized diagnostic and clinical settings. Large-scale studies need to be conducted to identify early biomarkers and optimization of diagnostic methods has to be established per population and geographical variation. This will not only help clinicians around the world to detect the coinfection in time but also will prepare them for future outbreaks of other potential pandemics.

Mucor in a Viral Land: A Tale of Two Pathogens.

Purpose: COVID-19 infection, its treatment, resultant immunosuppression, and pre-existing comorbidities have made patients vulnerable to secondary infections including mucormycosis. It is important to understand the presentation, temporal sequence, risk factors, and outcomes to undertake measures for prevention and treatment. Methods: We conducted a retrospective, interventional study on six consecutive patients with COVID-19 who developed rhino-orbital mucormycosis and were managed at two tertiary ophthalmic referral centers in India between August 1 and December 15, 2020. Diagnosis of mucormycosis was based on clinical features, culture, and histopathology from sinus biopsy. Patients were treated with intravenous liposomal amphotericin B with addition of posaconazole and surgical debridement of necrotic tissue. Results: All patients were male, mean age 60.5 ± 12 (46.2-73.9) years, type 2 diabetics with mean blood glucose level of 222.5 ± 144.4 (86-404) mg/dL. Except for one patient who was diagnosed with mucormycosis concurrently with COVID-19, all patients received systemic corticosteroids for the treatment of COVID-19. The mean duration between diagnosis of COVID-19 and development of symptoms of mucor was 15.6 ± 9.6 (3-42) days. All patients underwent endoscopic sinus debridement, whereas two patients required orbital exenteration. At the last follow-up, all six patients were alive, on antifungal therapy. Conclusion: Mucormycosis is a life-threatening, opportunistic infection, and patients with moderate to severe COVID-19 are more susceptible to it. Uncontrolled diabetes mellitus and use of corticosteroids increase the risk of invasive fungal infection with mucormycosis which can develop during the course of the illness or as a sequelae. High index of suspicion, early diagnosis, and appropriate management can improve survival.