Diagnosis of dementia is a challenge in populations with heterogeneous educational background.OBJECTIVE: To compare the accuracies of two delayed recall tests for the diagnosis of dementia in a community with high proportion of illiterates.METHOD: The delayed u11-200ps recall of a word list from the CERAD battery (DR-CERAD) was compared with the de
Elucidating colorectal cancer-associated bacteria through profiling of minimally perturbed tissue-associated microbiota
Sequencing-based interrogation of gut microbiota is a valuable approach for detecting microbes associated with colorectal cancer (CRC); however, such studies are often confounded by the effect of bowel preparation.In this study, we evaluated the viability of identifying CRC-associated aluminum lotion mucosal bacteria through centimeter-scale profil
Deep Learning-Based Transfer Learning for Classification of Skin Cancer
One of the major health concerns for human society is skin cancer.When the pigments producing skin color turn carcinogenic, this disease gets contracted.A skin cancer diagnosis is a challenging process for dermatologists as many skin cancer pigments may appear similar in appearance.Hence, early detection of lesions (which form the base of skin canc
First-In-Human Phase I Study Of A Dual mTOR Kinase And DNA-PK Inhibitor (CC-115) In Advanced Malignancy
Pamela Munster,1 Monica Mita,2 Amit Mahipal,3 John Nemunaitis,4 Christophe Massard,5 Tom Mikkelsen,6 Cristina Cruz,7 Luis Paz-Ares,8 Manuel Hidalgo,9 Dana Rathkopf,10 George Blumenschein Jr,11 David C Smith,12 Barbara Eichhorst,13 Tim Cloughesy,14 Ellen H Filvaroff,15 Shaoyi Li,16 Heather Raymon,17 Hans de Haan,15 Kristen Hege,15 Johanna C Bendell1
A physiology-based approach for estimation of mental fatigue levels with both high time resolution and high level of granularity
Mental fatigue (MF) monitoring is essential for eliminating accidents in high-risk tasks and providing better productivity management in daily work tasks involving human operators.Previous works only built MF monitoring systems with either high time resolution or high granularity level.We proposed a physiological-based approach to estimate MF Level