AIMC Topic: Humans

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Implementation of Anxiety UK's Ask Anxia Chatbot Service: Lessons Learned.

JMIR human factors
Chatbots are increasingly being applied in the context of health care, providing access to services when there are constraints on human resources. Simple, rule-based chatbots are suited to high-volume, repetitive tasks and can therefore be used effec...

An organic brain-inspired platform with neurotransmitter closed-loop control, actuation and reinforcement learning.

Materials horizons
Organic neuromorphic platforms have recently received growing interest for the implementation and integration of artificial and hybrid neuronal networks. Here, achieving closed-loop and learning/training processes as in the human brain is still a maj...

Missing data in amortized simulation-based neural posterior estimation.

PLoS computational biology
Amortized simulation-based neural posterior estimation provides a novel machine learning based approach for solving parameter estimation problems. It has been shown to be computationally efficient and able to handle complex models and data sets. Yet,...

A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification.

Frontiers in endocrinology
OBJECTIVE: This study aimed to construct a machine learning model using clinical variables and ultrasound radiomics features for the prediction of the benign or malignant nature of pancreatic tumors.

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning radiomics analyses for distinguishing insulinomas from non-functional pancreatic neuroendocrine tumors.

Frontiers in endocrinology
OBJECTIVES: To develop and validate radiomics models utilizing endoscopic ultrasonography (EUS) images to distinguish insulinomas from non-functional pancreatic neuroendocrine tumors (NF-PNETs).

UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation.

PloS one
Organ segmentation has become a preliminary task for computer-aided intervention, diagnosis, radiation therapy, and critical robotic surgery. Automatic organ segmentation from medical images is a challenging task due to the inconsistent shape and siz...

Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global scoping review.

PloS one
Machine learning (ML) and deep learning (DL) models are being increasingly employed for medical imagery analyses, with both approaches used to enhance the accuracy of classification/prediction in the diagnoses of various cancers, tumors and bloodborn...

Nature is resource, playground, and gift: What artificial intelligence reveals about human-Nature relationships.

PloS one
This paper demonstrates how artificial-intelligence language analysis can inform understanding of human-nature relationships and other social phenomena. We demonstrate three techniques by investigating relationships within the popular word2vec word e...

Using machine learning to distinguish between authentic and imitation Jackson Pollock poured paintings: A tile-driven approach to computer vision.

PloS one
Jackson Pollock's abstract poured paintings are celebrated for their striking aesthetic qualities. They are also among the most financially valued and imitated artworks, making them vulnerable to high-profile controversies involving Pollock-like pain...