Title: Data-Based Risk Assessment of Cancer Diseases for Life nsurance
Abstract:
Using US cancer registry data of SEER (Surveillance, Epidemiology, and End Results Program), data based analyses of prevalence, incidence, and survival rates are able for the medical risk assessment in life insurance. Statistical analyses of cancer patients and base population were performed using SEER*Stat from the US National Cancer Institute. The system provides multivariate restrictions of patient groups and subdivisions of outcomes. The lecture focuses on survival time analyses and additional calculations for the outcome of extra mortality rates of cancer patients in relation to base population. Based on these extra mortality rates, principles of underwriting decisions in life insurance will be presented.
By:
Dr. Ralf Lohse,
Underwriter at Hannover Reinsurance SE
1987-1992: Diploma economic sciences, Leibniz University Hannover
1997 – 2004: Doctor of economics, Institute for Risk and Insurance, Leibniz University Hannover
1993 – 1997: German Market Department, Hannover Reinsurance SE
1997 – 2000: Actuarial Service Department, Hannover Reinsurance SE
Since 2000: Life Risk Assessment, Hannover Reinsurance SE
Title:
The Assessment of Long-Term-Care, its Quality Assurance and Results -The German Perspective-
Abstract:
The consequences of demographic aging caused an impulse for German politics to establish an independent Social Long-Term-Care Insurance in 1995. Since then the assessment for long-term-care became stepwise more comprehensive to cover the bio-psycho-social needs of an increasing part of the population. Nowadays, about 3.3 Million persons receive benefits from this social insurance which help to cover a great part (but not in full) of financial and material support to overcome the impacts of long-term-care. About 2.5 Million persons are assessed every year with continuously increasing tendency by nursing experts working for the Statutory Medical Service mostly performing home visits. They assess the appropriate scores for mobility, cognitive and communicative abilities, behavior, attitudes, habits and psychic problems, self-sufficiency, coping and handling of requirements due to disease and therapy, management of everyday life and maintaining social contacts, adding up to one of 5 grades, the need for technical aids, flat conversion, therapeutic procedures, rehabilitation and educative support. The assessment guidelines and the monitoring of the quality of their realization are presented as well as the outcome for the Long-Term-Care Insurance on the federal level. Twenty-five years of Long-Term-Care Insurance have led to a well established and steadfast insurance but with increasing expenses as well as rising social security contributions to face the challenges of a human and dignified evening of life for an increasing part of the population.
by Prof. Dr. med. Wolfgang Seger,
past Medical Director of the Health and Long-Term-Care Advisory Board in Lower Saxony, Germany,
Chairman of the Medical Advisory Board of the Federal Rehabilitation Council, Germany
Title: Access to Opioids in Palliative Care in Low-and Middle-Income Countries:
The Case of Burkina-Faso
-How Can Blockchain and Internet of Things Assist? –
Abstract
Poor access to Healthcare delivery services remains challenging in Low-and Middle-Income Countries (LMIC). In Burkina-Faso (BF), a Sub-Saharan African (SSA) country, patients requiring palliative (PC) are especially facing poor access to pain drug such as morphine. Facing poor access to pain-alleviating medicine can severely impact the daily quality of life (QoL). On one hand, patients are experiencing poor opioids access. On another hand opioids abuse (with drug addiction), prescription falsification, fraud in the distribution, stock shortage are noticed.
This Speech, therefore, would focus on investigating the reasons underlying the poor access to opioids in palliative care in BF and suggestions to improve the poor access to opioids. Furthermore, a blockchain (BC) and the Internet of Things (IoT) based system to secure and improve opioids supply, distribution, and prescription will be proposed. The main objective is to enable the traceability of any opioids prescription, secure the supply and distribution.
Keywords: Poor Access to Healthcare, Drug Supply Chain, Drug Distribution, Palliative Care, Internet of Things for Healthcare, Blockchain for Healthcare, Quality of Life, Morphine Provision
Dr Thierry Oscar Edoh
is an associate and affiliated researcher at the University of Bonn (Germany)/ Department of Pharmacy, visiting associate lecturer at the Institute of Mathematics and Physics (IMSP)/University Abomey-Calavi, (Benin-Africa), visiting lecturer at IUT Lokossa (Benin-Africa), and an affiliated researcher at the Technical University of Munich/department of Applied Software Engineering (Germany). He is a guest lecturer at many African, Asian, and East European Universities. He received his Diploma in computer sciences from the Technical University of Munich in Germany and held a Ph.D. at the German Federal Army University, where he worked for several years on the improvement of rural health care provision and access to healthcare in developing countries using ITC systems.
He performed postdoctoral research at the University of Bonn (Germany)/department of pharmacy. He worked on Drug Regulatory Affairs with a focus on Knowledge discovery and Drug marketing authorization.
He is a member of IEEE.
Title: Artificial Intelligence-Based Diagnostic Tools for Screening of Retinal Abnormalities in Human Eye
A great challenge in biomedical engineering is the noninvasive assessment of the physiological changes occurring inside the human body. Specifically, detecting the abnormalities in the human eye is extremely difficult due to the various complexities associated with the process. Conventional disease identification techniques from retinal images are mostly dependent on manual intervention. Since human observation is highly prone to error, the success rate of these techniques is quite low. Hence, the necessity of automated techniques for disease identification is significantly high. In this research work, this problem is tackled by proposing Artificial Intelligence (AI) based automated disease identification techniques in retinal images. The proposed approaches are tested on abnormal retinal images from four categories such as Non-Proliferative Diabetic Retinopathy (NPDR), Central Retinal Vein Occlusion (CRVO), Choroidal Neo-Vascularisation Membrane (CNVM) and Central Serous Retinopathy (CSR).These techniques are analyzed in terms of classification accuracy, sensitivity, specificity, Positive Likelihood Ratio (PLR) and Negative Likelihood Ratio (NLR). Experimental results have been promising for these proposed techniques in terms of the performance measures.
By: Dr . D. Jude Hemanth
Received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. His research areas include Computational Intelligence and Image processing. He has authored more than 100 research papers in reputed SCIE indexed/Scopus indexed International Journals and International Conferences with leading publishers such as Elsevier, Springer, IEEE, etc. His Cumulative Impact Factor is more than 75. He has authored 1 book with (VDM-Verlag, Germany) and 21 edited books with reputed publishers such as Elsevier, Springer, IET and IOS Press.
He has been serving as Associate Editor of SCIE Indexed International Journals such as IEEE Access Journal (IEEE) and Journal of Intelligent and fuzzy systems (IOS Press). He serves as an Editorial Board member/Guest Editor of many journals with leading publishers such as Springer (Sensing and Imaging) and Inderscience (IJAIP, IJICT, IJCVR, IJBET). He is the series editor of “Biomedical Engineering” book series in Elsevier.
He has been also the organizing committee member of several international conferences across the globe such as Portugal, Romania, UK, Egypt, China, etc. He has delivered more than 50 Invited Lectures in International Conferences/workshops. He holds professional membership with IEEE Technical Committee on Neural Networks (IEEE Computational Intelligence Society) and IEEE Technical Committee on Soft Computing (IEEE Systems, Man and Cybernatics Society). He has completed 1 funded research project from CSIR, Govt. of India. He also serves as the “Research Scientist” of Computational Intelligence and Information Systems (CI2S) Lab, Argentina and RIADI Lab, Tunisia. Currently, he is working as Associate Professor in Department of ECE, Karunya University, Coimbatore, India.
Please for the proposition of workshops or keynotes contact ichsmt16@gmail.com Tel: +213550168666