Results 31 to 40 of about 1,141,752 (328)
Molecular Oncology, EarlyView.Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee +8 more
wiley +1 more source
Frontiers in Big DataInterpreting fundus images is an essential skill for detecting eye diseases, such as diabetic retinopathy (DR), one of the leading causes of visual impairment. However, the training of junior doctors relies on experienced ophthalmologists, who often lack
Sara-Jane Bittner +4 more
doaj +1 more source
Artificial intelligence/machine learning in diabetes care
Indian Journal of Endocrinology and Metabolism, 2019 Artificial intelligence/Machine learning (AI/ML) is transforming all spheres of our life, including the healthcare system. Application of AI/ML has a potential to vastly enhance the reach of diabetes care thereby making it more efficient. The huge burden of diabetes cases in India represents a unique set of problems, and provides us with a unique ...
Rajiv Singla +3 more
openaire +3 more sources
Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley +1 more source
IEEE AccessRadiology reports are often unstructured, containing ambiguous phrases and negations that make automated interpretation difficult. This paper introduces MedInsight Pro, a hybrid clinical NLP (Natural Language Processing) framework that fuses ...
Somesh Nandi +3 more
doaj +1 more source
Artificial intelligence and machine learning in haematology [PDF]
British Journal of Haematology, 2019 Artificial intelligence (AI) and Machine Learning (ML) are trending topics. AI is a broad term that represents the general concept of machines being able to carry out decision-making and perform human-like complex tasks, such as problem solving, understanding languages, recognizing voices and images and other “smart” tasks.
openaire +2 more sources
Rapid screening of staphylokinase protein variants using an unpurified cell‐free expression system
FEBS Open Bio, EarlyView.An unpurified cell‐free protein synthesis (CFPS) platform enables rapid functional screening of staphylokinase variants. Direct plasminogen‐activation assays performed in microplate format provide real‐time activity readouts, allowing rapid identification and ranking of variants with improved or reduced fibrinolytic activity without protein ...
Maria Tomková +3 more
wiley +1 more source
UrbanBlocks 3-D: A Genetic Algorithm-Based Semantic Zoning Framework for Smart Cities
IEEE AccessUrban planning faces critical challenges with 68% of the global population projected to live in cities by 2050, requiring intelligent zoning solutions for sustainable development.
Somesh Nandi +3 more
doaj +1 more source
Biological learning and artificial intelligence [PDF]
, 1994 It was once taken for granted that learning in animals and man could be explained with a simple set of general learning rules, but over the last hundred years, a substantial amount of evidence has been accumulated that points in a quite different ...
Balkenius, Christian
core +3 more sources
Examples of Artificial Perceptions in Optical Character Recognition and Iris Recognition
, 2012 This paper assumes the hypothesis that human learning is perception based, and consequently, the learning process and perceptions should not be represented and investigated independently or modeled in different simulation spaces.
A.M. Turing +6 more
core +1 more source