This is not the Texture you are looking for! Introducing Novel Counterfactual Explanations for Non-Experts using Generative Adversarial Learning

With the ongoing rise of machine learning, the need for methods for explaining decisions made by artificial intelligence systems is becoming a more and more important topic. Especially for image classification tasks, many state-of-the-art tools to explain such classifiers rely on visual highlighting of important areas of the input data. Contrary, counterfactual explanation systems try to enable a counterfactual reasoning by modifying the input image in a way such that the classifier would have made a different prediction. By doing so, the users of counterfactual explanation systems are equipped with a completely different kind of explanatory information. However, methods for generating realistic counterfactual explanations for image classifiers are still rare. In this work, we present a novel approach to generate such counterfactual image explanations based on adversarial image-to-image translation techniques. Additionally, we conduct a user study to evaluate our approach in a use case which was inspired by a healthcare scenario. Our results show that our approach leads to significantly better results regarding mental models, explanation satisfaction, trust, emotions, and self-efficacy than two state-of-the art systems that work with saliency maps, namely LIME and LRP

Alterfactual Explanations -- The Relevance of Irrelevance for Explaining AI Systems

Explanation mechanisms from the field of Counterfactual Thinking are a widely-used paradigm for Explainable Artificial Intelligence (XAI), as they follow a natural way of reasoning that humans are familiar with. However, all common approaches from this field are based on communicating information about features or characteristics that are especially important for an AI's decision. We argue that in order to fully understand a decision, not only knowledge about relevant features is needed, but that the awareness of irrelevant information also highly contributes to the creation of a user's mental model of an AI system. Therefore, we introduce a new way of explaining AI systems. Our approach, which we call Alterfactual Explanations, is based on showing an alternative reality where irrelevant features of an AI's input are altered. By doing so, the user directly sees which characteristics of the input data can change arbitrarily without influencing the AI's decision. We evaluate our approach in an extensive user study, revealing that it is able to significantly contribute to the participants' understanding of an AI. We show that alterfactual explanations are suited to convey an understanding of different aspects of the AI's reasoning than established counterfactual explanation methods.Comment: Accepted at IJCAI 2022 Workshop on XA

Prototyping a Tool for Processing Genetic Meta-Data in Microbiological Laboratories

Next generation sequencing (NGS) technologies allow improved understanding of pathogens. In the upstream processing of generating genomic data, there is still a lack of process-oriented tools for managing corresponding meta data. In this paper, we provide a description of how a process-oriented software prototype was developed that allowed the capture and collation of metadata involved when doing NGS. Our question was: How to develop an interactive web application that supports the process-oriented management of genetic data independent of any sequencing technique

Focal HIFU therapy for anterior compared to posterior prostate cancer lesions.

OBJECTIVE To compare cancer control in anterior compared to posterior prostate cancer lesions treated with a focal HIFU therapy approach. MATERIALS AND METHODS In a prospectively maintained national database, 598 patients underwent focal HIFU (Sonablate®500) (March/2007-November/2016). Follow-up occurred with 3-monthly clinic visits and PSA testing in the first year with PSA, every 6-12 months with mpMRI with biopsy for MRI-suspicion of recurrence. Treatment failure was any secondary treatment (ADT/chemotherapy, cryotherapy, EBRT, RRP, or re-HIFU), tumour recurrence with Gleason ≥ 3 + 4 on prostate biopsy without further treatment or metastases/prostate cancer-related mortality. Cases with anterior cancer were compared to those with posterior disease. RESULTS 267 patients were analysed following eligibility criteria. 45 had an anterior focal-HIFU and 222 had a posterior focal-HIFU. Median age was 64 years and 66 years, respectively, with similar PSA level of 7.5 ng/ml and 6.92 ng/ml. 84% and 82%, respectively, had Gleason 3 + 4, 16% in both groups had Gleason 4 + 3, 0% and 2% had Gleason 4 + 4. Prostate volume was similar (33 ml vs. 36 ml, p = 0.315); median number of positive cores in biopsies was different in anterior and posterior tumours (7 vs. 5, p = 0.009), while medium cancer core length, and maximal cancer percentage of core were comparable. 17/45 (37.8%) anterior focal-HIFU patients compared to 45/222 (20.3%) posterior focal-HIFU patients required further treatment (p = 0.019). CONCLUSION Treating anterior prostate cancer lesions with focal HIFU may be less effective compared to posterior tumours

Dynamic difficulty adjustment in virtual reality exergames through experience-driven procedural content generation

Virtual Reality (VR) games that feature physical activities have been shown to increase players' motivation to do physical exercise. However, for such exercises to have a positive healthcare effect, they have to be repeated several times a week. To maintain player motivation over longer periods of time, games often employ Dynamic Difficulty Adjustment (DDA) to adapt the game's challenge according to the player's capabilities. For exercise games, this is mostly done by tuning specific in-game parameters like the speed of objects. In this work, we propose to use experience-driven Procedural Content Generation for DDA in VR exercise games by procedurally generating levels that match the player's current capabilities. Not only finetuning specific parameters but creating completely new levels has the potential to decrease repetition over longer time periods and allows for the simultaneous adaptation of the cognitive and physical challenge of the exergame. As a proof-of-concept, we implement an initial prototype in which the player must traverse a maze that includes several exercise rooms, whereby the generation of the maze is realized by a neural network. Passing those exercise rooms requires the player to perform physical activities. To match the player's capabilities, we use Deep Reinforcement Learning to adjust the structure of the maze and to decide which exercise rooms to include in the maze. We evaluate our prototype in an exploratory user study utilizing both biodata and subjective questionnaires

Leukocyte-Reduced Platelet-Rich Plasma Alters Protein Expression of Adipose Tissue–Derived Mesenchymal Stem Cells

Background: Application of platelet-rich plasma and stem cells has become important in regenerative medicine. Recent literature supports the use of platelet-rich plasma as a cell culture media supplement to stimulate proliferation of adipose tissue-derived mesenchymal stem cells. The underlying mechanism of proliferation stimulation by platelet-rich plasma has not been investigated so far. Methods: Adipose tissue-derived mesenchymal stem cells were cultured in alpha-minimal essential medium supplemented with platelet-rich plasma or fetal calf serum. Cell proliferation was assessed with cell cycle kinetics using flow cytometric analyses after 48 hours. Differences in proteome expression of the adipose tissue-derived mesenchymal stem cells were analyzed using a reverse-phase protein array to quantify 214 proteins. Complementary Ingenuity Pathways Analysis and gene set enrichment analysis were performed using protein data, and confirmed by Western blot analysis. Results: A higher percentage of adipose tissue-derived mesenchymal stem cells in the S phase in the presence of platelet-rich plasma advocates the proliferation stimulation. Ingenuity Pathways Analysis and gene set enrichment analysis confirm the involvement of the selected proteins in the process of cell growth and proliferation. Ingenuity Pathways Analysis revealed a participation in the top-ranked canonical pathways PI3K/AKT, PTEN, ILK, and IGF-1. Gene set enrichment analysis identified the authors' protein set as being part of significantly regulated protein sets with the focus on cell cycle, metabolism, and the Kyoto Encyclopedia of Genes and Genomes transforming growth factor-beta signaling pathway. Conclusions: The present study provides evidence that platelet-rich plasma stimulates proliferation and induces a unique change in the proteomic profile of adipose tissue-derived mesenchymal stem cells. The interpretation of altered expression of regulatory proteins represents a step forward toward achieving good manufacturing practice-compliant criteria for cell-based strategies

Adipose Tissue-Derived Stem Cell Secreted IGF-1 Protects Myoblasts from the Negative Effect of Myostatin

Myostatin, a TGF-β family member, is associated with inhibition of muscle growth and differentiation and might interact with the IGF-1 signaling pathway. Since IGF-1 is secreted at a bioactive level by adipose tissue-derived mesenchymal stem cells (ASCs), these cells (ASCs) provide a therapeutic option for Duchenne Muscular Dystrophy (DMD). But the protective effect of stem cell secreted IGF-1 on myoblast under high level of myostatin remains unclear. In the present study murine myoblasts were exposed to myostatin under presence of ASCs conditioned medium and investigated for proliferation and apoptosis. The protective effect of IGF-1 was further examined by using IGF-1 neutralizing and receptor antibodies as well as gene silencing RNAi technology. MyoD expression was detected to identify impact of IGF-1 on myoblasts differentiation when exposed to myostatin. IGF-1 was accountable for 43.6% of the antiapoptotic impact and 48.8% for the proliferative effect of ASCs conditioned medium. Furthermore, IGF-1 restored mRNA and protein MyoD expression of myoblasts under risk. Beside fusion and transdifferentiation the beneficial effect of ASCs is mediated by paracrine secreted cytokines, particularly IGF-1. The present study underlines the potential of ASCs as a therapeutic option for Duchenne muscular dystrophy and other dystrophic muscle diseases