Part of Springer Nature. For example, CNs including graphene, graphene oxide, carbon nanotubes, and fullerenes can act as efficient photosensitizer carriers for cancer treatment. Each paper will be assigned a minimum of two reviewers to ensure the highest possible quality. While the field of biomaterials is well-established, numerous developments are emerging in the field, and the purpose of this special issue is to capture these emergent elements. Editorial on 2020 biomaterials special issue, https://doi.org/10.1007/s42247-020-00121-1. This review examines how combination of PDT and PTT with carbonaceous nanomaterials (CNs) offers additional active complementary and supplementary roles for deep tumors in cancer therapy. Seven extended papers were selected from among all the accepted papers by the special issue guest editors Yingxia Shao, Yanyan Shen, Bin Cui, and Jeffrey Xu Yu, based on the relevance to the journal and the reviews of the conference version of the papers. - 149.62.169.56. The seven extended papers cover a variety of topics related to database, data science and engineering. special issue ASCO 2020 Preface Dear Colleagues, Although the COVID-19 pandemic has prevented on-site attendance of the world’s largest cancer conference this year, the experts’ avid interest in ad-vances in their respective areas of specialization remains unchanged. Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. This review offers valuable insight regarding the authors’ perceptions of limitations to the field, which can inform future research. The first two articles refer to droughts and the other six articles cover topics ranging from extreme climate-driven processes linked to precipitation to flood risk assessments in rural/urban areas and the effects of climate change. Therefore, the bioaerosol is widely concerned. A second paper within this physiological response topic is contributed by Shruti Agarwalla et al., which discusses the application of graphene-based materials to reduce the incidence of infection at implant sites. Artificial Intelligence in Pattern Recognition, Experiment: Gamification of interactive Machine Learning (giML), Experiment: Interactive Machine Learning for the Traveling-Salesman-Problem, Project EMPAIA – Ecosystem for Pathology Diagnostics with AI Assistance, Springer LNAI xxAI – Beyond explainable Artificial Intelligence, Special Issue Springer/Nature BMC Medical Informatics & Decision Making – Explainable-AI, Springer LNAI 12090 – AI/Machine Learning for Digital Pathology, LNAI 9605 Machine Learning for Health Informatics, LNAI Hot Topics in integrative Machine Learning & Knowledge Extraction (iMAKE), LNCS 8401 Interactive KDD in Biomedical Informatics, XXAI @ ICML 2020 Extending Explainable AI Beyond Deep Models and Classifiers, Explainable AI conference session exAI 2019, WS Secure Federated Machine Learning for Health Informatics, March, 1-2, 2018, 10@Reggio – Privacy Aware Machine Learning, 09@Salzburg – Privacy Aware Machine Learning, WS Machine Learning for Biomed @ TUGraz Jan, 26, 2016, HCAI Research Seminar (course of 2020/21), LV 185.A83 Machine Learning for Health Informatics (Class of 2020), LV 185.A83 Machine Learning for Health Informatics (Class of 2019), LV 706.315 From explainable AI to Causability (class of 2019), Mini Course MAKE-Decisions – with practice (class of 2019), LV 706.046 AK HCI 2019: Intelligent UI: towards explainable AI, Mini Course: From Data Science to interpretable AI (class of 2019), Mini Course MAKE-Decisions – with practice (WS 2018), LV 706.046 AK HCI 2018: Intelligent UI: to explainable AI, LV 185.A83 Machine Learning for Health Informatics class 2018, LV 185.A83 Machine Learning for Health Informatics class 2017, Mini-Course Machine Learning Knowledge Extraction Verona, LV 706.046 AK HCI: Intelligent UI with Challenge 2017, LV 706.315 Interactive Machine Learning (iML), LV 706.997/998 PhD Seminar Welcome Students, LV 706.046 Selected Topics of HCI: Intelligent UI, LV 185.A83 Machine Learning for Health Informatics class 2016, LV 340.300 Principles of Interaction – iML, LV 706.315 Methods of explainable AI (ex-AI class 2018). We would like to acknowledge the work done by all the authors and their willingness to contribute their papers to this special issue. The last day for submission of all contributions to the special issue is 30th June, 2020. Data Sci. Authors should select Special Issue: Bioaerosol, Environment and Health. Tanya Braun, Institute of Information Systems, University of Lübeck, Lübeck, GermanyDr. Keywordsartificial intelligence, machine learning, deep learning. - 67.227.191.225. Part II, Yunmook N, Bin C, Sang-Won L, Jeffrey XY, Yang-Sae M, Steven EW (2020) Database Systems for Advanced Applications—Proceedings of the 25th International conference, DASFAA 2020, Jeju, South Korea, September 24–27, Part III, Beijing University of, Posts and Telecommunications, Beijing, China, Shanghai Jiao Tong University, Shanghai, China, The Chinese University of Hong Kong, Hong Kong, China, You can also search for this author in PubMed Google Scholar. With this special collection we want to inspire cross-domain experts interested in artificial intelligence/machine learning to stimulate research, engineering and evaluation in, around and for explainable AI – towards making machine decisions transparent, re-enactive, comprehensible, interpretable, thus explainable, re-traceable and reproducible; the latter is the cornerstone of scientific research per se, and it is of utmost importance for decision support. #KANDINSKYPatterns our Swiss-Knife for the study of explainable-AI, FWF Project Reference Model of Explainable AI for the Medical Domain, EU Project HEAP – Human Exposome Assessment Platform, EU Project FeatureCloud (Federated Machine Learning), Project MAKEpatho – Machine Learning & Knowledge Extraction in Digital Pathology, Project TUGROVIS – Tumor-Growth Simulation and Visualization, Project GRAPHINIUS – Interactive Graph Research Framework, Project iML interactive Machine Learning with the Human-in-the-Loop, Experiment: Human Intelligence vs. Furthermore, research in this field is becoming more global, with participation from more countries in Asia and the Middle East beyond the traditional contributions of Europe and North America. Revealing Cluster Structures through AMTICS” proposed a novel and efficient visualization approach to interactively and fast mine coarse insights in very dynamic and rapid changing applications. These materials can decrease microorganism viability and biofilm formation, and are poised to emerge as candidates for new preventative and therapeutic strategies to decrease infection-related failure of implanted materials and devices. All contributions must not have been previously published or be under consideration for publication elsewhere. volume 5, pages331–332(2020)Cite this article. Philosophical, neural, and didactic investigations of conceptual, graphical representations, Human and machine reasoning under inconsistency, Human and machine knowledge representation and uncertainty, Automated decision-making and argumentation, Conceptual structures in natural language processing and linguistics, Resource allocation and agreement technologies. Call for Papers: Special Issue on Conceptual Structures 2020 This Special Issue grew out of the International Conference on Conceptual Structures “Ontologies and Concepts in Mind and Machine” … The first “Exploiting Latent Semantic Subspaces to Derive Associations for Specific Pharmaceutical Semantics” presented an approach to extract interpretable latent semantic subspace from the neural-embedding models in the biomedical domain. Manuscripts are invited addressing accommodations and modifications, embedded-instruction, co-teaching, paraprofessional support, …

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