Increasing Performance And Sample Efficiency With Model-agnostic Interactive Feature Attributions

Model-agnostic feature attributions can provide local insights in complex ML models. If the explanation is correct, a domain expert can validate and trust the model's decision. However, if it contradicts the expert's knowledge, related work only corrects irrelevant features to improve the model. To allow for unlimited interaction, in this paper we provide model-agnostic implementations for two popular explanation methods (Occlusion and Shapley values) to enforce entirely different attributions in the complex model. For a particular set of samples, we use the corrected feature attributions to generate extra local data, which is used to retrain the model to have the right explanation for the samples. Through simulated and real data experiments on a variety of models we show how our proposed approach can significantly improve the model's performance only by augmenting its training dataset based on corrected explanations. Adding our interactive explanations to active learning settings increases the sample efficiency significantly and outperforms existing explanatory interactive strategies. Additionally we explore how a domain expert can provide feature attributions which are sufficiently correct to improve the model

CoRe-Sleep: A Multimodal Fusion Framework for Time Series Robust to Imperfect Modalities

Sleep abnormalities can have severe health consequences. Automated sleep staging, i.e. labelling the sequence of sleep stages from the patient's physiological recordings, could simplify the diagnostic process. Previous work on automated sleep staging has achieved great results, mainly relying on the EEG signal. However, often multiple sources of information are available beyond EEG. This can be particularly beneficial when the EEG recordings are noisy or even missing completely. In this paper, we propose CoRe-Sleep, a Coordinated Representation multimodal fusion network that is particularly focused on improving the robustness of signal analysis on imperfect data. We demonstrate how appropriately handling multimodal information can be the key to achieving such robustness. CoRe-Sleep tolerates noisy or missing modalities segments, allowing training on incomplete data. Additionally, it shows state-of-the-art performance when testing on both multimodal and unimodal data using a single model on SHHS-1, the largest publicly available study that includes sleep stage labels. The results indicate that training the model on multimodal data does positively influence performance when tested on unimodal data. This work aims at bridging the gap between automated analysis tools and their clinical utility.Comment: 10 pages, 4 figures, 2 tables, journa

Comparative aspects of pulmonary toxicity induced by cytotoxic agents with emphasis on lomustine, and a veterinary case report

In veterinary oncology the use of the nitrosourea compound lomustine is increasing. veterinary oncologists need to be aware of the pulmonary toxicity of this drug. Because of the lack of veterinary publications on this subject, the incidence and pathophysiology in human cancer patients of pulmonary toxicity induced by cytotoxic agents in general and by nitrosoureas in particular are discussed. Three clinical syndromes can be recognized, the most devastating of which is interstitial pneumonitis resulting in pulmonary fibrosis. Disturbances in the homeostatic mechanisms of the oxidant/antioxidant-, immunologic-, matrix repair-, proteolytic-, and central nervous systems are some of the major mechanisms of pulmonary injury in human medicine. Risk factors such as cumulative dose, age, radiation, oxygen administration and multi-drug regimens are recognized. For the first time in veterinarv medicine, a case report of a dog with pulmonary fibrosis, probably caused by chronic lomustine administration, is presented

Peri-articular histiocytic sarcoma and synovial cell sarcoma in Bernese Mountain dogs : a retrospective investigation of the prevalence of these tumours in association with previously diseased joints

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