AIMC Topic: Humans

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A review on current advances in machine learning based diabetes prediction.

Primary care diabetes
Diabetes is a metabolic disorder comprising of high glucose level in blood over a prolonged period in the body as it is not capable of using it properly. The severe complications associated with diabetes include diabetic ketoacidosis, nonketotic hype...

Neuromorphic Binarized Polariton Networks.

Nano letters
The rapid development of artificial neural networks and applied artificial intelligence has led to many applications. However, current software implementation of neural networks is severely limited in terms of performance and energy efficiency. It is...

Toward assessing clinical trial publications for reporting transparency.

Journal of biomedical informatics
OBJECTIVE: To annotate a corpus of randomized controlled trial (RCT) publications with the checklist items of CONSORT reporting guidelines and using the corpus to develop text mining methods for RCT appraisal.

Face the Uncanny: The Effects of Doppelganger Talking Head Avatars on Affect-Based Trust Toward Artificial Intelligence Technology are Mediated by Uncanny Valley Perceptions.

Cyberpsychology, behavior and social networking
This experiment ( = 228) examined how exposure to a talking head doppelganger created by an artificial intelligence (AI) program influenced affect-based trust toward AIs. Using a 3 (talking head featuring the participant's or a stranger's face, audio...

Androgen Receptor Binding Category Prediction with Deep Neural Networks and Structure-, Ligand-, and Statistically Based Features.

Molecules (Basel, Switzerland)
Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain developm...

LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) employing inertial motion data has gained considerable momentum in recent years, both in research and industrial applications. From the abstract perspective, this has been driven by an acceleration in the building of ...

Diffusion histology imaging differentiates distinct pediatric brain tumor histology.

Scientific reports
High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation o...

Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study.

Journal of medical Internet research
BACKGROUND: During a pandemic, it is important for clinicians to stratify patients and decide who receives limited medical resources. Machine learning models have been proposed to accurately predict COVID-19 disease severity. Previous studies have ty...