Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Noora Neittaanmäki"'
Autor:
Sirkku Peltonen, Jørgen Serup, Mimmi Tang, Martin Gillstedt, Despoina Kantere, Noora Neittaanmäki, Peter Holmström, Jaishri O. Blakeley, Karli Rosner, Joshua Roberts, Torsten Bove, Katrine Elisabeth Karmisholt
Publikováno v:
JEADV Clinical Practice, Vol 3, Iss 4, Pp 1049-1060 (2024)
Abstract Background High‐intensity focused ultrasound (HIFU) is widely used in the treatment of deep tumours, but clinical trials on skin tumours are not yet available. Neurofibromatosis Type I (NF1) is among the most common single‐gene inherited
Externí odkaz:
https://doaj.org/article/5e9e8b36be6f452284504c556955ef46
Publikováno v:
Diagnostic Pathology, Vol 19, Iss 1, Pp 1-8 (2024)
Abstract Background Surgical excision with clear histopathological margins is the preferred treatment to prevent progression of lentigo maligna (LM) to invasive melanoma. However, the assessment of resection margins on sun-damaged skin is challenging
Externí odkaz:
https://doaj.org/article/8d471c7b41234f5da5dc92e72c75e172
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionNodal metastasis (NM) in sentinel node biopsies (SNB) is crucial for melanoma staging. However, an intra-nodal nevus (INN) may often be misclassified as NM, leading to potential misdiagnosis and incorrect staging. There is high discordanc
Externí odkaz:
https://doaj.org/article/9b8853912a7448cb872af4e6c8051ea4
Publikováno v:
Diagnostic Pathology, Vol 19, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/6d23bb23bdf24500b0fcb1937df0d758
Autor:
Filmon Yacob, Jan Siarov, Kajsa Villiamsson, Juulia T. Suvilehto, Lisa Sjöblom, Magnus Kjellberg, Noora Neittaanmäki
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract The high incidence rates of basal cell carcinoma (BCC) cause a significant burden at pathology laboratories. The standard diagnostic process is time-consuming and prone to inter-pathologist variability. Despite the application of deep learni
Externí odkaz:
https://doaj.org/article/94608c9e506c4ed089b9ef674c7b36c3
Autor:
Filmon Yacob, Jan Siarov, Kajsa Villiamsson, Juulia T. Suvilehto, Lisa Sjöblom, Magnus Kjellberg, Noora Neittaanmäki
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-2 (2023)
Externí odkaz:
https://doaj.org/article/c3da9c803d714c61b17dc0a0981c5b27
Autor:
John Paoli, Ilkka Pölönen, Mari Salmivuori, Janne Räsänen, Oscar Zaar, Sam Polesie, Sari Koskenmies, Sari Pitkänen, Meri Övermark, Kirsi Isoherranen, Susanna Juteau, Annamari Ranki, Mari Grönroos, Noora Neittaanmäki
Publikováno v:
Acta Dermato-Venereologica, Vol 102 (2022)
Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma
Externí odkaz:
https://doaj.org/article/adc91d9e963340aea808faff1468fdf0
Publikováno v:
Acta Dermato-Venereologica, Vol 101, Iss 2, p adv00405 (2021)
Pigmented basal cell carcinomas can be difficult to distinguish from melanocytic tumours. Hyperspectral imaging is a non-invasive imaging technique that measures the reflectance spectra of skin in vivo. The aim of this prospective pilot study was to
Externí odkaz:
https://doaj.org/article/0cce763b8bb34c2e93c50b87063f98ea
Autor:
Sam Polesie, Phillip H. McKee, Jerad M. Gardner, Martin Gillstedt, Jan Siarov, Noora Neittaanmäki, John Paoli
Publikováno v:
Frontiers in Medicine, Vol 7 (2020)
Background: Artificial intelligence (AI) has recently surfaced as a research topic in dermatology and dermatopathology. In a recent survey, dermatologists were overall positive toward a development with an increased use of AI, but little is known abo
Externí odkaz:
https://doaj.org/article/6afa6f0b7d51487bae202197512ca52d
Autor:
Oscar Zaar, Alexander Larson, Sam Polesie, Karim Saleh, Mikael Tarstedt, Antonio Olives, Andrea Suárez, Martin Gillstedt, Noora Neittaanmäki
Publikováno v:
Acta Dermato-Venereologica, Vol 100, Iss 16, p adv00260 (2020)
Artificial intelligence (AI) algorithms for automated classification of skin diseases are available to the consumer market. Studies of their diagnostic accuracy are rare. We assessed the diagnostic accuracy of an open-access AI application (Skin Imag
Externí odkaz:
https://doaj.org/article/90ab79f81a054f9b886ff3f504a649d5