AIMC Topic: Artificial Intelligence

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Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology.

Seminars in diagnostic pathology
Digital pathology has a crucial role in diagnostic pathology and is increasingly a technological requirement in the field. Integration of digital slides into the pathology workflow, advanced algorithms, and computer-aided diagnostic techniques extend...

Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints: A Pilot Study.

International journal of environmental research and public health
The diagnostic accuracy of differential diagnoses generated by artificial intelligence (AI) chatbots, including the generative pretrained transformer 3 (GPT-3) chatbot (ChatGPT-3) is unknown. This study evaluated the accuracy of differential-diagnosi...

Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries.

Scientific reports
Most artificial intelligence (AI) research and innovations have concentrated in high-income countries, where imaging data, IT infrastructures and clinical expertise are plentiful. However, slower progress has been made in limited-resource environment...

A low-power and flexible bioinspired artificial sensory neuron capable of tactile perceptual and associative learning.

Journal of materials chemistry. B
Biomimetic haptic neuron systems have received a lot of attention from the booming artificial intelligence industry for their wide applications in personal health monitoring, electronic skin, and human-machine interfaces. In this work, inspired by th...

Scientific novelty beyond the experiment.

Microbial biotechnology
Practical experiments drive important scientific discoveries in biology, but theory-based research studies also contribute novel-sometimes paradigm-changing-findings. Here, we appraise the roles of theory-based approaches focusing on the experiment-d...

Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review.

Journal of nephrology
OBJECTIVES: In this systematic review we aimed at assessing how artificial intelligence (AI), including machine learning (ML) techniques have been deployed to predict, diagnose, and treat chronic kidney disease (CKD). We systematically reviewed the a...

Integrating Computation, Experiment, and Machine Learning in the Design of Peptide-Based Supramolecular Materials and Systems.

Angewandte Chemie (International ed. in English)
Interest in peptide-based supramolecular materials has grown extensively since the 1980s and the application of computational methods has paralleled this. These methods contribute to the understanding of experimental observations based on interaction...

A Review of Emerging Electromagnetic-Acoustic Sensing Techniques for Healthcare Monitoring.

IEEE transactions on biomedical circuits and systems
Conventional electromagnetic (EM) sensing techniques such as radar and LiDAR are widely used for remote sensing, vehicle applications, weather monitoring, and clinical monitoring. Acoustic techniques such as sonar and ultrasound sensors are also used...