Scientific Program

Conference Series LLC Ltd invites all the participants across the globe to attend 13th International Conference on Dementia and Vascular Dementia Zurich, Switzerland.

Day 1 :

  • Vascular Dementia, Dementia

Session Introduction

Boaz Lerner

Professor of Machine Learning at Ben-Gurion University, Israel

Title: Insights from a Machine Learning Perspective into Amyotrophic Lateral Sclerosis and other Neurodegenerative Diseases

Boaz Lerner is a Professor of Machine Learning at Ben-Gurion University, where he also did his Ph.D. After Ph.D., he did research at Aston University and Cambridge University. Lerner has been investigating, developing, teaching, and consulting in machine learning, undertaking many projects funded by, or in co-operation with, different agencies/authorities/companies. He has been a reviewer for many journals and conferences and has served on various conference PCs. Lerner has supervised around 50 graduate students and has published around 100 papers in peer-reviewed journals and conference proceedings. Current main interests are in Bayesian network structure learning, precision medicine, and precision agriculture.


Objective: ALS disease state prediction usually assumes linear progression and uses a classifier evaluated by its accuracy. Since disease progression is not linear, and the accuracy cannot tell large from small prediction errors, we dispense with the linearity assumption and apply ordinal classification. We identify the most influential variables in predicting and explaining the disease. In contrast to conventional modeling of the patient's total functionality, we model separate patient functionalities (e.g., in walking or speaking). We extend our system to other neurodegenerative diseases (ND), e.g., Parkinson’s (PD) and Alzheimer’s (AD).

Methods: We introduce ordinal classifiers that already during training account for error severity in predicting the disease state in the last clinic visit for 3,772 patients in the PRO-ACT database. We use feature-selection methods and the classifiers to determine the most influential variables in predicting the disease from demographic, clinical, and laboratory data collected in different clinic visits, and interrelations among these variables and their relations with the disease state. We apply these machine-learning (ML) methods to: 1) model ALS patient functionalities; 2) diagnose PD and AD; and 3) predict PD severity.

Results: We show that ordinal classifiers outperform classifiers that do not account for error severity. We identify clinical and lab test variables important to ALS prediction, and specific value combinations of these variables that occur more frequently in patients with severe deterioration than in patients with mild deterioration and vice versa. Further, we accurately predict AD, PD, and PD severity from data using ML.

Conclusions: Ordinal classification of ALS state is superior to conventional classification. Important ALS variables and their interrelations help explain disease mechanism. By modeling separate patient functionalities, variables and their connections to different aspects of the disease are related to different body segments. We conclude that ML methods can successfully help ND analysis from data.

Rahul Hajare

Principal of Ishwar Deshmukh Institute of Pharmacy, india

Title: How to raise the loud voice of common Indian women

Dr. Rahul Hajare has been a hard worker all his academic life. After his Ph.D in Pharmacy from VMRF Salem which he completed with flying colours, he is fortunate to work NARI primer HIV research Institute to complete Post Docunder the of World Renowned Scientist Respected Dr. R.S.Paranjape., Retired Director & Scientist ‘G’ National AIDS Research Institute Pune. Dr. Rahul Hajare has Associate Professor of Pharmaceutical Medical Chemistry to Pune University (until 2020), he has serviced three times AssociateProfessor in Pharmaceutical Science and Analytical Science. Graduated from Amravati University in 2003, after an assignment he worked as an M.Pharm Scholar in the Institute of Pharmaceutical Education and Research passed with distinction, he has Post Graduate Teacher for Master of Pharmacy, he has more than 30 scientific and methodological works, 3 patents of scientific research.

Dr. Rahul Hajare now Principal of Ishwar Deshmukh Institute of Pharmacy affiliated combined Amravati University and All India Council of Technical education New Delhi.


Why do we in our society refuse to talk about the same thing that caused us to be born? Most women appreciate it when their partners want to make sure their needs are met.  The harder you work to please her, the greater the chance she will reciprocate. We have all heard that women 'fake it', but did you know how many? According Psychology Today website, only about 25% of women said they orgasm regularly during sex -- certainly not a number that inspires confidence in the sexual prowess of the average male. Evidently, it doesn’t matter whether you’re from the land of the Kama Sutra or the home of KY Jelly; the numbers suggest that if you’re a man engaging in regular sex, you’re probably not doing a good enough job. Fortunately, and contrary to what most of you are afraid of hearing, it isn’t the size of the ship that matters, but the motion of the ocean. Even more simply put, how you’re doing is all about what you’re doing. So, in the spirit of literally helping out our fellow man, here are a few pointers on how to make sex more pleasurable for your partner.