AIMC Topic: Neural Networks, Computer

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SeeSaw: Learning Soft Tissue Deformation From Laparoscopy Videos With GNNs.

IEEE transactions on bio-medical engineering
A major challenge in image-guided laparoscopic surgery is that structures of interest often deform and go, even if only momentarily, out of view. Methods which rely on having an up-to-date impression of those structures, such as registration or local...

Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data.

Sensors (Basel, Switzerland)
The health, safety, and well-being of household pets such as cats has become a challenging task in previous years. To estimate a cat's behavior, objective observations of both the frequency and variability of specific behavior traits are required, wh...

Enhanced MobileNet for skin cancer image classification with fused spatial channel attention mechanism.

Scientific reports
Skin Cancer, which leads to a large number of deaths annually, has been extensively considered as the most lethal tumor around the world. Accurate detection of skin cancer in its early stage can significantly raise the survival rate of patients and r...

Detection of hate: speech tweets based convolutional neural network and machine learning algorithms.

Scientific reports
There is no doubt that social media sites have provided many benefits to humanity, such as sharing information continuously and communicating with others easily. It also seems that social media sites have many advantages, but in addition to these adv...

In-context learning enables multimodal large language models to classify cancer pathology images.

Nature communications
Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this process is computationally and technically demanding. In language processin...

AI-driven segmentation of the pulp cavity system in mandibular molars on CBCT images using convolutional neural networks.

Clinical oral investigations
OBJECTIVE: To develop and validate an artificial intelligence (AI)-driven tool for automated segmentation of the pulp cavity system of mandibular molars on cone-beam computed tomography (CBCT) images.

Computer-aided diagnosis of early-stage Retinopathy of Prematurity in neonatal fundus images using artificial intelligence.

Biomedical physics & engineering express
Retinopathy of Prematurity (ROP) is a retinal disorder affecting preterm babies, which can lead to permanent blindness without treatment. Early-stage ROP diagnosis is vital in providing optimal therapy for the neonates. The proposed study predicts ea...

Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models.

PLoS computational biology
Measles is an important infectious disease system both for its burden on public health and as an opportunity for studying nonlinear spatio-temporal disease dynamics. Traditional mechanistic models often struggle to fully capture the complex nonlinear...

Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form.

PloS one
BACKGROUND AND OBJECTIVE: Detecting patients at high risk of occurrence of an Invasive Disease Event after a first diagnosis of breast cancer, such as recurrence, distant metastasis, contralateral tumor and second tumor, could support clinical decisi...

Towards efficient IoT communication for smart agriculture: A deep learning framework.

PloS one
The integration of IoT (Internet of Things) devices has emerged as a technical cornerstone in the landscape of modern agriculture, revolutionising the way farming practises are viewed and managed. Smart farming, enabled by interconnected sensors and ...