AIMC Topic: Humans

Clear Filters Showing 13061 to 13070 of 95995 articles

Community Graph Convolution Neural Network for Alzheimer's Disease Classification and Pathogenetic Factors Identification.

IEEE transactions on neural networks and learning systems
As a complex neural network system, the brain regions and genes collaborate to effectively store and transmit information. We abstract the collaboration correlations as the brain region gene community network (BG-CN) and present a new deep learning a...

Future prospective of AI in drug discovery.

Advances in pharmacology (San Diego, Calif.)
Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and lower productivity in pharmaceutical industries, to discover effective drugs and their development. ...

Deep learning: A game changer in drug design and development.

Advances in pharmacology (San Diego, Calif.)
The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artificial intelligence. Deep learning technologies expedite the procedure, increasing treatment success rates and speeding life-saving procedures. Deep lear...

The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses.

Frontiers in public health
INTRODUCTION: Speech impediments (SIs) are increasingly prevalent among middle-aged and older adults, raising concerns within public health. Early detection of potential SI in this demographic is critical. This study investigates the potential of Act...

Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data.

PloS one
Regarding the transportation of people, commodities, and other items, aeroplanes are an essential need for society. Despite the generally low danger associated with various modes of transportation, some accidents may occur. The creation of a machine ...

A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning.

PloS one
Autonomous transportation systems have the potential to greatly impact the way we travel. A vital aspect of these systems is their connectivity, facilitated by intelligent transport applications. However, the safety ensured by the vehicular network c...

LazyAct: Lazy actor with dynamic state skip based on constrained MDP.

PloS one
Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. Specifically, each decision made by a...

Machine learning-based analyzing earthquake-induced slope displacement.

PloS one
Accurately evaluating earthquake-induced slope displacement is a key factor for designing slopes that can effectively respond to seismic activity. This study evaluates the capabilities of various machine learning models, including artificial neural n...

Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients.

PloS one
BACKGROUND: A second primary malignant tumor is one of the most important factors affecting the long-term survival of young women with breast cancer (YWBC). As one of the main treatments for breast cancer YWBC patients, postoperative radiotherapy (PO...

Why do people resist AI-based autonomous cars?: Analyzing the impact of the risk perception paradigm and conditional value on public acceptance of autonomous vehicles.

PloS one
This study examines the factors that lead to the acceptance of AI-based autonomous vehicles. Despite the considerable importance of AI-based autonomous vehicles there has been a lack of analysis based on theoretical models and analysis that considers...