Predicting the amputation risk for patients with diabetic foot ulceration - a Bayesian decision support tool. - Jens Hüsers; Guido Hafer; Jan Heggemann; Stefan Wiemeyer; Swen Malte John; Ursula Hübner (BMC Medical Informatics Decis. Mak., 2020)

Development and Evaluation of a Bayesian Risk Stratification Method for Major Amputations in Patients with Diabetic Foot Ulcers. - Jens Hüsers; Guido Hafer; Jan Heggemann; Stefan Wiemeyer; Swen Malte John; Ursula Hübner (ICIMTH, 2021)

Automatic Classification of Diabetic Foot Ulcer Images - A Transfer-Learning Approach to Detect Wound Maceration. - Jens Hüsers; Guido Hafer; Jan Heggemann; Stefan Wiemeyer; Mareike Przysucha; Joachim Dissemond; Maurice Moelleken; Cornelia Erfurt-Berge; Ursula Hübner (ICIMTH, 2021)

Automatic Wound Type Classification with Convolutional Neural Networks. - Leila Malihi; Jens Hüsers; Mats L. Richter; Maurice Moelleken; Mareike Przysucha; Dorothee Busch; Jan Heggemann; Guido Hafer; Stefan Wiemeyer; Gunther Heidemann; Joachim Dissemond; Cornelia Erfurt-Berge; et al. (ICIMTH, 2022)

An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers. - Jens Hüsers; Maurice Moelleken; Mats L. Richter; Mareike Przysucha; Leila Malihi; Dorothee Busch; Nina-Alexandra Götz; Jan Heggemann; Guido Hafer; Stefan Wiemeyer; Birgit Babitsch; Gunther Heidemann; et al. (MIE, 2022)

Can Synthetic Images Improve CNN Performance in Wound Image Classification? - Leila Malihi; Ursula Hübner; Mats L. Richter; Maurice Moelleken; Mareike Przysucha; Dorothee Busch; Jan Heggemann; Guido Hafer; Stefan Wiemeyer; Gunther Heidemann; Joachim Dissemond; Cornelia Erfurt-Berge; et al. (MIE, 2023)