AIMC Topic: Humans

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A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity.

Accident; analysis and prevention
Pedestrians represent a population of vulnerable road users who are directly exposed to complex traffic conditions, thereby increasing their risk of injury or fatality. This study first constructed a multidimensional indicator to quantify pedestrian ...

Artificial intelligence for drug discovery and development in Alzheimer's disease.

Current opinion in structural biology
The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the development of effective therapeutics or prevention strategies. Artificial Intelligence (AI)-guided drug discovery combined with genetics/multi-omics (genomics...

Using deep neural networks to disentangle visual and semantic information in human perception and memory.

Nature human behaviour
Mental representations of familiar categories are composed of visual and semantic information. Disentangling the contributions of visual and semantic information in humans is challenging because they are intermixed in mental representations. Deep neu...

Spatial relation categorization in infants and deep neural networks.

Cognition
Spatial relations, such as above, below, between, and containment, are important mediators in children's understanding of the world (Piaget, 1954). The development of these relational categories in infancy has been extensively studied (Quinn, 2003) y...

Enhancing inclusive education in the UAE: Integrating AI for diverse learning needs.

Research in developmental disabilities
INTRODUCTION: Artificial Intelligence (AI) mediated systems have become important in educational set-ups, and it is still debatable whether or not they can be useful in special needs education. This qualitative research scrutinizes the experiences an...

Do large language models show decision heuristics similar to humans? A case study using GPT-3.5.

Journal of experimental psychology. General
A Large Language Model (LLM) is an artificial intelligence system trained on vast amounts of natural language data, enabling it to generate human-like responses to written or spoken language input. Generative Pre-Trained Transformer (GPT)-3.5 is an e...

Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images.

Computers in biology and medicine
Artificial intelligence (AI)-assisted diagnosis is an ongoing revolution in pathology. However, a frequent drawback of AI models is their propension to make decisions based rather on bias in training dataset than on concrete biological features, thus...

Single-port vs multi-port robot-assisted partial nephrectomy: A single center propensity score-matched analysis.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION AND OBJECTIVES: The aim of the study is to compare key outcomes of Single-Port (SP) and Multi-Port (MP) robot-assisted partial nephrectomy (RAPN).

Engineering novel scaffolds for specific HDAC11 inhibitors against metabolic diseases exploiting deep learning, virtual screening, and molecular dynamics simulations.

International journal of biological macromolecules
The prevalence of metabolic diseases is increasing at a frightening rate year by year. The burgeoning development of deep learning enables drug design to be more efficient, selective, and structurally novel. The critical relevance of Histone deacetyl...