@article{RamserBaurKelleretal.2021,
  author    = {Ramser, Michaela and Baur, Johannes and Keller, Nicola and Kukleta, Jan F. and D{\"o}rfer, J{\"o}rg and Wiegering, Armin and Eisner, Lukas and Dietz, Ulrich A.},
  title     = {Robotic hernia surgery I. English version},
  series = {Der Chirurg},
  volume    = {92},
  journal   = {Der Chirurg},
  number    = {Suppl 1},
  doi       = {10.1007/s00104-021-01446-1},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-323934},
  pages     = {S1-S13},
  year      = {2021},
  abstract  = {The treatment of inguinal hernias with open and minimally invasive procedures has reached a high standard in terms of outcome over the past 30 years. However, there is still need for further improvement, mainly in terms of reduction of postoperative seroma, chronic pain, and recurrence. This video article presents the endoscopic anatomy of the groin with regard to robotic transabdominal preperitoneal patch plasty (r‑TAPP) and illustrates the surgical steps of r‑TAPP with respective video sequences. The results of a cohort study of 302 consecutive hernias operated by r‑TAPP are presented and discussed in light of the added value of the robotic technique, including advantages for surgical training. r‑TAPP is the natural evolution of conventional TAPP and has the potential to become a new standard as equipment availability increases and material costs decrease. Future studies will also have to refine the multifaceted added value of r‑TAPP with new parameters.},
  language  = {en}
}
@article{NedopilDhaliwalHowelletal.2022,
  author    = {Nedopil, Alexander J. and Dhaliwal, Anand and Howell, Stephen M. and Hull, Maury L.},
  title     = {A surgeon that switched to unrestricted kinematic alignment with manual instruments has a short learning curve and comparable resection accuracy and outcomes to those of an experienced surgeon},
  series = {Journal of Personalized Medicine},
  volume    = {12},
  journal   = {Journal of Personalized Medicine},
  number    = {7},
  issn      = {2075-4426},
  doi       = {10.3390/jpm12071152},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281842},
  year      = {2022},
  abstract  = {After starting an orthopedic practice, a surgeon with a fellowship in mechanically aligned (MA) TKA initiated this study to characterize their learning curve after they switched to unrestricted kinematic alignment (KA) TKA using manual instruments. Accordingly, the present study determined for the inexperienced (IE) surgeon the number of cases required to achieve consistent femoral resections and operating times, and whether the femoral resection accuracy, patient-reported outcome measures (PROMs), and component alignment were different from an experienced (E) surgeon. This prospective cohort study analyzed the IE surgeon's first 30 TKAs, all performed with KA, and 30 consecutive KA TKAs performed by an E surgeon. The resection accuracy or deviation was the calipered thickness of the distal and posterior medial and lateral femoral resections minus the planned resection thickness, which was the thickness of the corresponding condyle of the femoral component, minus 2 mm for cartilage wear, and 1 mm for the kerf of the blade. Independent observers recorded the femoral resection thickness, operative times, PROMs, and alignment. For each femoral resection, the deviation between three groups of patients containing ten consecutive KA TKAs, was either insignificant (p = 0.695 to 1.000) or within the 0.5 mm resolution of the caliper, which indicated no learning curve. More than three groups were needed to determine the learning curve for the operative time; however, the IE surgeon's procedure dropped to 77 min for the last 10 patients, which was 20 min longer than the E surgeon. The resection deviations of the IE and E surgeon were comparable, except for the posterolateral femoral resection, which the IE surgeon under-resected by a mean of -0.8 mm (p < 0.0001). At a mean follow-up of 9 and 17 months, the Forgotten Joint Score, Oxford Knee Score, KOOS, and the alignment of the components and limbs were not different between the IE and E surgeon (p ≥ 0.6994). A surgeon that switches to unrestricted KA with manual instruments can determine their learning curve by computing the deviation of the distal and posterior femoral resections from the planned resection. Based on the present study, an IE surgeon could have resection accuracy, post-operative patient outcomes, and component alignment comparable to an E surgeon.},
  language  = {en}
}
@article{PamirSzyszkaScheineretal.2014,
  author    = {Pamir, Evren and Szyszka, Paul and Scheiner, Ricarda and Nawrot, Martin P.},
  title     = {Rapid learning dynamics in individual honeybees during classical conditioning},
  series = {Frontiers in Behavioral Neuroscience},
  volume    = {8},
  journal   = {Frontiers in Behavioral Neuroscience},
  number    = {313},
  issn      = {1662-5153},
  doi       = {10.3389/fnbeh.2014.00313},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-115365},
  year      = {2014},
  abstract  = {Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.},
  language  = {en}
}