New Developments in Bacterial, Viral, and Fungal Cutaneous Infections

Yeroushalmi, Samuel; Shirazi, Joshua Yoseph; Friedman, Adam

doi:10.1007/s13671-020-00295-1

Cited by 8 publications

(2 citation statements)

References 112 publications

(93 reference statements)

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“…These infections include erysipelas, trauma-related infections, skin ulcers etc. These skin infections are spread further, and their severity may create health issues like fever and pain or without pain [69]. In some cases, symptoms of skin diseases are rashes; these rashes are used to diagnose certain diseases like rubella, measles, chickenpox, and erythema infectiosum [58].…”

Section: Overview Of Skin Layers and Theirmentioning

confidence: 99%

Analysis, Prediction and Classification of Skin Cancer using Artificial Intelligence - A Brief Study and Review

Pandala,

S. Periyanayagi

2023

SCPE

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World Health Organization (WHO) records that skin cancer has vigorously affected people in recent decades. Worldwide, many people are affected by skin cancer, and its affected count will increase yearly. Hence, skin cancer has become a threatening disease. Skin cancer prediction at an earlier time is becoming the higher priority and most challenging task worldwide. A computer-based diagnosis is needed to perform the automatic prognosis of skin cancer. It assists dermatologists in many ways, including the prediction of skin cancer at the earlier stages, easy to diagnose and effective. Nowadays, artificial intelligence based machine learning approaches have been implemented for an early prediction of cancer in the skin through medical images. This paper is focused on a detailed, comprehensive review of skin cancer analysis, forecast, and algorithmic-based procedures for classifying skin diseases. Moreover, this review paper focused on various stages of algorithm approaches for skin tumor detection like pre-processing data, segmenting data, feature selection, and disease classifier. This detailed review of neoplasm diseases like cancer on the skin is done based on machine and deep learning algorithms to help further research.

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Section: Overview Of Skin Layers and Theirmentioning

confidence: 99%

Analysis, Prediction and Classification of Skin Cancer using Artificial Intelligence - A Brief Study and Review

Pandala,

S. Periyanayagi

2023

SCPE

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“…The most predominant types of skin lesions in everyday infectious disease practice are skin and soft tissue infections caused by bacteria, viruses, fungi and parasites, and different types of exanthems presenting with fever [5][6][7][8]. Skin and soft tissue infections are among the most widespread types of infections and include cellulitis, erysipelas, impetigo, Life 2022, 12, 978 2 of 12 ecthyma, folliculitis, furuncles, carbuncles, abscesses, trauma-related infections, decubital ulcers, necrotizing fasciitis, Fournier gangrene and infections from human or animal bites.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Types of Skin Lesions and Diseases in Everyday Infectious Disease Practice—How Experienced Are We?

Skuhala

Trkulja

Rimac

et al. 2022

Life

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Rashes and skin lesions are a common reason for patient visits to emergency departments and physicians' offices. The differential diagnosis includes a variety of infectious and non-infectious diseases, some of which can be life-threatening. The aim of this retrospective study was to evaluate the quantity and type of skin lesions among outpatients and inpatients at a tertiary care university-affiliated teaching hospital for infectious diseases over a three-year period to assess disease burden and physicians’ experience in diagnosing skin lesions. Diagnoses (by ICD-10 codes) were classified into three groups: infectious diseases that include skin lesions, non-infectious skin lesions and undiagnosed skin lesions. During the observed period, out of the total of 142,416 outpatients, 14.8% presented with some form of skin lesion. Among them, 68% had skin lesions inherent to infectious disease, 10.8% suffered from non-infectious skin lesions and 21.2% remained with undiagnosed skin lesions. The most common infectious diagnoses were chickenpox, herpes zoster and unspecified viral infections characterized by skin and mucous membrane lesions. The most common non-infectious diagnoses were urticaria and atopic dermatitis. Overall, the most common individual diagnosis (ICD-10 code) was “nonspecific skin eruption” (n = 4448, 21.1%), which was followed by chickenpox and herpes zoster. Among the 17,401 patients hospitalized over the observed period, 13.1% had skin lesion as the main reason for hospitalization, almost all (97.5%) of which were infectious in etiology. The most common diagnoses were cellulitis, erysipelas and herpes zoster. The presented data suggest that the burden of diseases presenting with skin lesions is significant in everyday infectious disease practice, but the overwhelming number of undiagnosed patients implies the need for further education in this area.

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Acne in the first three decades of life: An update of a disorder with profound implications for all decades of life

et al. 2021

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New Developments in Bacterial, Viral, and Fungal Cutaneous Infections

Cited by 8 publications

References 112 publications

Analysis, Prediction and Classification of Skin Cancer using Artificial Intelligence - A Brief Study and Review

Analysis, Prediction and Classification of Skin Cancer using Artificial Intelligence - A Brief Study and Review

Analysis of Types of Skin Lesions and Diseases in Everyday Infectious Disease Practice—How Experienced Are We?

Acne in the first three decades of life: An update of a disorder with profound implications for all decades of life

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