Rainer Hofmann‐Wellenhof: Influence Statistics

Rainer Hofmann‐Wellenhof

Rainer Hofmann‐Wellenhof

Department of Dermatology, Medical University of Graz, Graz, Austria | Department of Dermatology, Medical University of Graz, Graz, Austria. | Department of Dermatology and ...

Rainer Hofmann‐Wellenhof: Expert Impact

Concepts for which Rainer Hofmann‐Wellenhof has direct influence: Confocal microscopy , Image analysis , Scalp naevi , Reflectance confocal microscopy , Normal skin , Melanocytic nevi , Skin cancer .

Rainer Hofmann‐Wellenhof: KOL impact

Concepts related to the work of other authors for which for which Rainer Hofmann‐Wellenhof has influence: Skin cancer , Confocal microscopy , Dermoscopic features , Basal cell carcinoma , Actinic keratosis , Melanocytic lesions , Cutaneous melanoma .

KOL Resume for Rainer Hofmann‐Wellenhof

Year
2021

Department of Dermatology, Medical University of Graz, Graz, Austria

Abteilung für Dermatologie und Venerologie, Medizinische Universität Graz, Graz, Österreich

2020

Universitätsklinik für Dermatologie, Medizinische Universität Graz, Graz, Österreich

Department of Dermatology, Medical University of Graz, Graz, Germany

Medical University of Graz, Graz, Austria

2019

Department of Dermatology, University Hospital Graz, Graz, Austria

Univ.-Klinik für Dermatologie & Venerologie, Medizinische Universität Graz, Graz, Österreich

2018

Department of Dermatology, Graz Medical University, Graz, Austria

Universitätsklinik für Dermatologie und Venerologie, Medizinische Universität Graz, Auenbruggerplatz 8, 8036, Graz, Österreich

2017

Department of Dermatology Medical University of Graz Graz Austria

2016

Department of Dermatology, Medical University Graz, Graz, Austria

Universitätsklinik für Dermatologie und Venerologie Medizinische Universität Graz Österreich

2015

Department of Dermatology, University of Graz, Graz, Austria.

Division of Dermatology and Venereology, Medical University of Graz, Graz, Austria

2014

Department Dermatology, University Graz, Graz, Austria

Klinik für Dermatologie und Venerologie, Medizinische Universität Graz, Graz, Österreich

2013

Departments of Dermatology (Drs Arzberger, Massone, and Hofmann-Wellenhof) and Environmental Dermatology and Venereology (Dr Komericki), Medical University of Graz, Graz, Austria

2012

Professor of Dermatology, Department of Dermatology, University of Graz, Austria

2011

Clinical Professor, Department of Dermatology, New York University School of Medicine, New York, NY, USA

Director, Cockerell and Associates Dermpath Diagnostics

Division of Dermatology, Medical University of Graz, Graz, Austria

Department of Dermatology, Medical University of Graz

2010

Department of Dermatology (Drs Frühauf, Ambros-Rudolph, Weger, Ahlgrimm-Siess, Salmhofer, and Hofmann-Wellenhof) and Institute for Medical Informatics, Statistics and Documentation (Mr Schwantzer), Medical University of Graz, Graz, Austria.

2009

Division of Oncology, Department of Internal Medicine, *Department of Dermatology and †Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 15, A‐8036 Graz, Austria

Department of Dermatology (Drs Binder, Salmhofer, and Hofmann-Wellenhof), Medical University of Graz (Mss Kroemer and Custovic)

Abteilung für Dermatologie und Venerologie, Medizinische Universität Graz, Österreich

2008

Department of Dermatology, Medical University of Graz, 8036 Graz, Austria

Forschungseinheit Teledermatologie, Abteilung für Allgemeine Dermatologie, Universitäts‐Hautklinik, Medizinische Universität Graz

2007

Department of Dermatology, Medical University of Graz; Graz, Austria

2006

Universitätsklinik für Dermatologie und Venerologie,Medizinische Universität Graz,Austria

Department of Dermatology, Medical University of Graz, Graz, Austria (Drs Kolm, Hofmann-Wellenhof, Fink-Puches, Wolf, Richtig, Smolle, Kerl, Soyer, and Zalaudek)

2005

Department of Dermatology and, Institute for Medical Informatics, Statistics and Documentation, University of Graz, Graz, Austria

2004

Departments of Dermatology, Second University of Naples, Naples, Italy (Drs Argenziano, Cicale, Petrillo, and Ruocco), and Medical University of Graz, Graz, Austria (Drs Zalaudek, Hofmann-Wellenhof, and Soyer)

Department of Dermatology, University of Graz, Graz, Austria
*Department of Dermatology, Second University of Naples, Via S. Pansini 5, I‐80131 Naples, Italy
†Department of Dermatology, University Tor Vergata, Rome, Italy
‡Department of Dermatology, Melanoma Unit, Hospital Clinic, IDIBAPS, Barcelona, Spain
§Division of Preventive Oncology, Centro di Riferimento Oncologico, Aviano, Italy
¶Dermatology Unit, Hotel Dieu de Lyon, Lyon, France

University of Graz, Graz, Austria.

2003

Universitäts-Hautklinik Graz, Österreich

(1) Department of Dermatology, University of Graz, Austria 
 (2) Department of Dermatology, Second University of Naples, Naples, Italy 
 
Received: 12. 11. 2002 | Accepted: 26. 3. 2003

Department of Dermatology, University of Graz, Graz, Austria;, Department of Dermatology, Second University of Naples, Naples, Italy

2002

Department of Dermatology, University of Graz, A-8036 Graz, Austria

Prominent publications by Rainer Hofmann‐Wellenhof

KOL-Index: 14199 . BACKGROUND: Preliminary studies have described morphological features of basal cell carcinoma (BCC) imaged by high-definition optical coherence tomography (HD-OCT) and suggested that this technique may aid in its diagnosis and management. However, systematic studies evaluating the accuracy of HD-OCT for the diagnosis of BCC are lacking. OBJECTIVE: The aim of this study was to identify ...
Known for Optical Coherence | Basal Cell Carcinoma | Bcc Subtypes | Hd Oct
KOL-Index: 14119 . BACKGROUND: Preliminary studies described morphological features of actinic keratosis (AK) and squamous cell carcinoma (SCC) imaged by High-Definition Optical Coherence Tomography (HD-OCT) and suggested that this technique may aid in their diagnosis. However, systematic studies evaluating the accuracy of HD-OCT for the diagnosis of AK and SCC are lacking so far. OBJECTIVE: In this study, ...
Known for Normal Skin | Optical Coherence | Actinic Keratosis | Squamous Cell Carcinoma
KOL-Index: 11738 . Exposing human skin to ultraviolet radiation causes DNA damage, sunburn, immune alterations, and eventually, skin cancer. We wished to determine whether liposomes containing a DNA repair enzyme could prevent any of the acute effects of irradiation when applied after ultraviolet exposure. Fifteen human patients with a prior history of skin cancer were exposed to two minimal erythema doses ...
Known for T4 Endonuclease | Necrosis Factor | Topical Treatment | Human Skin
KOL-Index: 11555 . Importance: Deep learning convolutional neural networks (CNNs) have shown a performance at the level of dermatologists in the diagnosis of melanoma. Accordingly, further exploring the potential limitations of CNN technology before broadly applying it is of special interest. Objective: To investigate the association between gentian violet surgical skin markings in dermoscopic images and the ...
Known for Dermoscopic Images | Diagnostic Performance | Melanoma Recognition | Skin Markings
KOL-Index: 10874 . BACKGROUND: There is a need for better standardization of the dermoscopic terminology in assessing pigmented skin lesions. OBJECTIVE: The virtual Consensus Net Meeting on Dermoscopy was organized to investigate reproducibility and validity of the various features and diagnostic algorithms. METHODS: Dermoscopic images of 108 lesions were evaluated via the Internet by 40 experienced ...
Known for Pigmented Skin Lesions | Consensus Meeting | Diagnostic Algorithms | Basal Cell Diagnosis
KOL-Index: 10823 . BACKGROUND: Convolutional neural networks (CNNs) efficiently differentiate skin lesions by image analysis. Studies comparing a market-approved CNN in a broad range of diagnoses to dermatologists working under less artificial conditions are lacking. MATERIALS AND METHODS: One hundred cases of pigmented/non-pigmented skin cancers and benign lesions were used for a two-level reader study in ...
Known for Skin Lesions | Cnn Dermatologists | Sensitivity Specificity | Neural Network
KOL-Index: 10631 . BACKGROUND: Several dermoscopic and in vivo reflectance confocal microscopy (RCM) diagnostic criteria of lentigo maligna (LM)/lentigo maligna melanoma (LMM) have been identified. However, no study compared the diagnostic accuracy of these techniques. OBJECTIVE: We evaluated the diagnostic accuracy of dermoscopy and RCM for LM/LMM using a holistic assessment of the images. METHODS: A total ...
Known for Confocal Microscopy | Lm Lmm | Dermoscopy Rcm | Lentigo Maligna
KOL-Index: 10362 . BACKGROUND: Benign melanocytic skin lesions may be difficult to differentiate from melanoma both clinically and dermoscopically. One of the most confounding dermoscopic features, commonly seen in melanoma but in our experience also in melanocytic naevi, is represented by the so-called blue-white structures (BWS). OBJECTIVES: To evaluate diagnostic significance and histopathological ...
Known for Skin Lesions | Melanocytic Naevi | Histopathological Correlates | Spontaneous Nevus
KOL-Index: 9944 . BACKGROUND: Based on the dermoscopic classification of acquired melanocytic naevi, six different dermoscopic types can be distinguished by morphology (globular, globular-reticular, globular-homogeneous, reticular, reticular-homogeneous, homogeneous) and by pigment distribution (uniform, central hyperpigmentation, central hypopigmentation, peripheral hyperpigmentation, peripheral ...
Known for Melanocytic Naevi | Dermoscopy Patterns | Dermoscopic Types | Individuals Age
KOL-Index: 9285 . IMPORTANCE: The comparative diagnostic performance of dermoscopic algorithms and their individual criteria are not well studied. OBJECTIVES: To analyze the discriminatory power and reliability of dermoscopic criteria used in melanoma detection and compare the diagnostic accuracy of existing algorithms. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective, observational study of 477 ...
Known for Dermoscopic Criteria | Abcd Rule | Differentiate Nevi | Melanoma Detection
KOL-Index: 9094 . BACKGROUND: Superficial BCCs (sBCCs) usually appear as multiple lesions in chronic sun-damaged skin of elderly people and may show a destructive growth if left untreated. Non-invasive treatment modalities, such as cryotherapy have been employed for sBCCs, all failing to provide tissue for confirming diagnosis and assessing adequacy of tumour removal. Reflectance confocal microscopy (RCM), ...
Known for Confocal Microscopy | Basal Cell | Vivo Reflectance | Cryotherapy Treatment
KOL-Index: 9049 . BACKGROUND: Skin self-examinations supplemented with mobile teledermoscopy might improve early detection of skin cancers compared with naked-eye skin self-examinations. We aimed to assess whether mobile teledermoscopy-enhanced skin self-examination can improve sensitivity and specificity of self-detection of skin cancers when compared with naked-eye skin self-examination. METHODS: This ...
Known for Skin Cancer | Participants Intervention | Controlled Trial | Sensitivity Specificity
KOL-Index: 8948 . BACKGROUND: Even though progress has been made, the detection of melanoma still poses a challenge. In light of this situation, the Nevisense electrical impedance spectroscopy (EIS) system (SciBase AB, Stockholm, Sweden) was designed and shown to have the potential to be used as an adjunct diagnostic tool for melanoma detection. OBJECTIVES: To assess the effectiveness and safety of the ...
Known for Melanoma Detection | Clinical Performance | Observed Sensitivity | Basal Cell Carcinoma
KOL-Index: 8904 . BACKGROUND: The dermoscopic classification is a useful tool for handling patients with atypical naevi (Clark naevi). OBJECTIVES: To investigate if the dermoscopic classification of atypical naevi is of any value to discriminate benign from malignant melanocytic lesions. METHODS: Consecutive patients (n = 205) were included with 254 suspicious melanocytic lesions, confirmed by ...
Known for Melanocytic Lesions | Threestructure Type | Dermoscopic Images | Clark Naevi

Key People For Confocal Microscopy

Top KOLs in the world
#1
Milind M Rajadhyaksha
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#2
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#3
Roger Yonchien Tsien
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#4
Watt W Webb
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#5
Pellacani Pellacani
confocal microscopy actinic keratosis basal cell
#6
Caterina Longo
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Department of Dermatology, Medical University of Graz, Graz, Austria | Department of Dermatology, Medical University of Graz, Graz, Austria. | Department of Dermatology and Venereology, Medical University of Graz, Graz, Austria | Abteilung für Dermat