AIMC Topic: Benchmarking

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Semi-supervised medical image classification via distance correlation minimization and graph attention regularization.

Medical image analysis Feb 21, 2024
We propose a novel semi-supervised learning method to leverage unlabeled data alongside minimal annotated data and improve medical imaging classification performance in realistic scenarios with limited labeling budgets to afford data annotations. Our...
Supervised Machine Learning Benchmarking Neural Networks, Computer Humans
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Evaluating Large Language Models for the National Premedical Exam in India: Comparative Analysis of GPT-3.5, GPT-4, and Bard.

JMIR medical education Feb 21, 2024
BACKGROUND: Large language models (LLMs) have revolutionized natural language processing with their ability to generate human-like text through extensive training on large data sets. These models, including Generative Pre-trained Transformers (GPT)-3...
Confusion Educational Status Artificial Intelligence Benchmarking India Humans
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Graph Neural Network contextual embedding for Deep Learning on tabular data.

Neural networks : the official journal of the International Neural Network Society Feb 16, 2024
All industries are trying to leverage Artificial Intelligence (AI) based on their existing big data which is available in so called tabular form, where each record is composed of a number of heterogeneous continuous and categorical columns also known...
Humans Benchmarking Big Data Artificial Intelligence Neural Networks, Computer Deep Learning
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A Review of deep learning methods for denoising of medical low-dose CT images.

Computers in biology and medicine Feb 15, 2024
To prevent patients from being exposed to excess of radiation in CT imaging, the most common solution is to decrease the radiation dose by reducing the X-ray, and thus the quality of the resulting low-dose CT images (LDCT) is degraded, as evidenced b...
Humans Deep Learning Image Processing, Computer-Assisted Tomography, X-Ray Computed Algorithms Signal-To-Noise Ratio Benchmarking
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Capacity of Generative AI to Interpret Human Emotions From Visual and Textual Data: Pilot Evaluation Study.

JMIR mental health Feb 6, 2024
BACKGROUND: Mentalization, which is integral to human cognitive processes, pertains to the interpretation of one's own and others' mental states, including emotions, beliefs, and intentions. With the advent of artificial intelligence (AI) and the pro...
Humans Artificial Intelligence Benchmarking Eye Emotions Pilot Projects
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Identifying Diabetic Retinopathy in the Human Eye: A Hybrid Approach Based on a Computer-Aided Diagnosis System Combined with Deep Learning.

Tomography (Ann Arbor, Mich.) Feb 5, 2024
Diagnosing and screening for diabetic retinopathy is a well-known issue in the biomedical field. A component of computer-aided diagnosis that has advanced significantly over the past few years as a result of the development and effectiveness of deep ...
Benchmarking Diabetes Mellitus Computers Diabetic Retinopathy Deep Learning Diagnosis, Computer-Assisted Humans
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A Novel Multi-Scale Graph Neural Network for Metabolic Pathway Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Feb 5, 2024
Predicting the metabolic pathway classes of compounds in the human body is an important problem in drug research and development. For this purpose, we propose a Multi-Scale Graph Neural Network framework, named MSGNN. The framework includes a subgrap...
Neural Networks, Computer Humans Benchmarking
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Improving preliminary clinical diagnosis accuracy through knowledge filtering techniques in consultation dialogues.

Computer methods and programs in biomedicine Jan 30, 2024
BACKGROUND AND OBJECTIVE: Symptom descriptions by ordinary people are often inaccurate or vague when seeking medical advice, which often leads to inaccurate preliminary clinical diagnoses. To address this issue, we propose a deep learning model named...
United States Natural Language Processing Language Humans Knowledge Bases Referral and Consultation Benchmarking
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DEPICTER: Deep representation clustering for histology annotation.

Computers in biology and medicine Jan 26, 2024
Automatic segmentation of histopathology whole-slide images (WSI) usually involves supervised training of deep learning models with pixel-level labels to classify each pixel of the WSI into tissue regions such as benign or cancerous. However, fully s...
Benchmarking Supervised Machine Learning Cluster Analysis Workload Image Processing, Computer-Assisted
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Evidence-based uncertainty-aware semi-supervised medical image segmentation.

Computers in biology and medicine Jan 24, 2024
Semi-Supervised Learning (SSL) has demonstrated great potential to reduce the dependence on a large set of annotated data, which is challenging to collect in clinical practice. One of the most important SSL methods is to generate pseudo labels from t...
Supervised Machine Learning Uncertainty Benchmarking Image Processing, Computer-Assisted
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