AIMC Topic: Neural Networks, Computer

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Generative pretrained transformer-4, an artificial intelligence text predictive model, has a high capability for passing novel written radiology exam questions.

International journal of computer assisted radiology and surgery Feb 21, 2024
PURPOSE: AI-image interpretation, through convolutional neural networks, shows increasing capability within radiology. These models have achieved impressive performance in specific tasks within controlled settings, but possess inherent limitations, s...
Artificial Intelligence Databases, Factual Humans Neural Networks, Computer Radiology
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Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units.

Journal of chemical information and modeling Feb 21, 2024
Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the deve...
Algorithms Communication Intelligence Acceleration Neural Networks, Computer
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Prediction of monthly evapotranspiration by artificial neural network model development with Levenberg-Marquardt method in Elazig, Turkey.

Environmental science and pollution research international Feb 21, 2024
The phenomenon of evapotranspiration (ET) is closely linked to the issue of water scarcity, as it involves water loss through both evaporation and plant transpiration. Accurate prediction of evapotranspiration is of utmost importance in the strategic...
Algorithms Water Neural Networks, Computer Turkey Agricultural Irrigation
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SynerGNet: A Graph Neural Network Model to Predict Anticancer Drug Synergy.

Biomolecules Feb 21, 2024
Drug combination therapy shows promise in cancer treatment by addressing drug resistance, reducing toxicity, and enhancing therapeutic efficacy. However, the intricate and dynamic nature of biological systems makes identifying potential synergistic d...
Combined Modality Therapy Drug Therapy, Combination Artificial Intelligence Antineoplastic Agents Humans Neural Networks, Computer
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Learning representations for image-based profiling of perturbations.

Nature communications Feb 21, 2024
Measuring the phenotypic effect of treatments on cells through imaging assays is an efficient and powerful way of studying cell biology, and requires computational methods for transforming images into quantitative data. Here, we present an improved s...
Neural Networks, Computer
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Ensemble of deep convolutional neural networks is more accurate and reliable than board-certified ophthalmologists at detecting multiple diseases in retinal fundus photographs.

The British journal of ophthalmology Feb 21, 2024
AIMS: To develop an algorithm to classify multiple retinal pathologies accurately and reliably from fundus photographs and to validate its performance against human experts.
Diabetic Retinopathy Neural Networks, Computer Humans Fundus Oculi Macular Degeneration Ophthalmologists Glaucoma Deep Learning
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Age and sex estimation in cephalometric radiographs based on multitask convolutional neural networks.

Oral surgery, oral medicine, oral pathology and oral radiology Feb 20, 2024
OBJECTIVES: Age and sex characteristics are evident in cephalometric radiographs (CRs), yet their accurate estimation remains challenging due to the complexity of these images. This study aimed to harness deep learning to automate age and sex estimat...
Sex Determination by Skeleton Age Determination by Skeleton Child Cephalometry Sensitivity and Specificity Humans Female Deep Learning Male Neural Networks, Computer Adolescent Adult
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Biopsy or Follow-up: AI Improves the Clinical Strategy of US BI-RADS 4A Breast Nodules Using a Convolutional Neural Network.

Clinical breast cancer Feb 20, 2024
OBJECTIVES: To develop predictive nomograms based on clinical and ultrasound features and to improve the clinical strategy for US BI-RADS 4A lesions.
Retrospective Studies Female Aged Adult Humans Neural Networks, Computer Nomograms Follow-Up Studies Deep Learning Ultrasonography, Mammary Breast Neoplasms Biopsy ROC Curve Breast Middle Aged
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A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.

Medical & biological engineering & computing Feb 20, 2024
In recent years, fatigue driving has become the main cause of traffic accidents, leading to increased attention towards fatigue detection systems. However, the pooling and strided convolutional operations in fatigue detection algorithm based on tradi...
Fatigue Algorithms Deep Learning Humans Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted
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Enhancing adversarial attacks with resize-invariant and logical ensemble.

Neural networks : the official journal of the International Neural Network Society Feb 20, 2024
In black-box scenarios, most transfer-based attacks usually improve the transferability of adversarial examples by optimizing the gradient calculation of the input image. Unfortunately, since the gradient information is only calculated and optimized ...
Neural Networks, Computer Probability
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