Machine learning and artificial intelligence

All Items

• How Does a Convolutional Neural Network Trained to Differentiate between Invasive Melanoma and Melanoma In situ Generalize when Assessing Dysplastic Naevi?

  Martin Gillstedt, Klara Segerholm, Ludwig Mannius, John Paoli, Sam Polesie

  adv00891

• Risk of Non-cutaneous Cancers in Individuals with Basal Cell Carcinoma: A Population-based Cohort Study

  Hanna Kuru, Jari Jokelainen, Kaisa Tasanen, Laura Huilaja

  adv00826

• Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions

  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

  adv00815
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  Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network

  Martin Gillstedt, Ludwig Mannius, John Paoli, Johan Dahlén Gyllencreutz, Julia Fougelberg, Eva Johansson Backman, Jenna Pakka, Oscar Zaar, Sam Polesie

  adv00790
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  Ability to Predict Melanoma Within 5 Years Using Registry Data and a Convolutional Neural Network: A Proof of Concept Study

  Martin Gillstedt, Sam Polesie

  adv00750

• Hidradenitis Suppurativa International Online Community: Patient Characteristics and a Novel Model of Treatment Effectiveness

  Jen Barak-Levitt, Ron Held, Yossi Synett, Noa Kremer, Emmilia Hodak, Shany Sherman

  adv00686

• Deep Learning-based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia

  Meng Gao, Yue Wang, Haipeng Xu, Congcong Xu, Xianhong Yang, Jin Nie, Ziye Zhang, Zhixuan Li, Wei Hou, Yiqun Jiang

  adv00635