AIMC Topic: Deep Learning

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A fusocelular skin dataset with whole slide images for deep learning models.

Scientific data
Cutaneous spindle cell (CSC) lesions encompass a spectrum from benign to malignant neoplasms, often posing significant diagnostic challenges. Computer-aided diagnosis systems offer a promising solution to make pathologists' decisions objective and fa...

A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.

Neuroscience
Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the options for the treatment of VS, with the preservation of facial nerve (FN) function being the primary objective. Therefore, postoperative FN function pre...

Deep learning for cerebral vascular occlusion segmentation: A novel ConvNeXtV2 and GRN-integrated U-Net framework for diffusion-weighted imaging.

Neuroscience
Cerebral vascular occlusion is a serious condition that can lead to stroke and permanent neurological damage due to insufficient oxygen and nutrients reaching brain tissue. Early diagnosis and accurate segmentation are critical for effective treatmen...

Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.

Tomography (Ann Arbor, Mich.)
According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people's lives, particularly c...

Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer.

Biomedical engineering online
BACKGROUND: The study aimed at developing and validating a deep learning (DL) model based on the ultrasound imaging for predicting the platinum resistance of patients with epithelial ovarian cancer (EOC).

Rethinking femoral neck anteversion assessment: a novel automated 3D CT method compared to traditional manual techniques.

BMC musculoskeletal disorders
PURPOSE: To evaluate the accuracy and reliability of a novel automated 3D CT-based method for measuring femoral neck anteversion (FNA) compared to three traditional manual methods.

AI-IoT based smart agriculture pivot for plant diseases detection and treatment.

Scientific reports
There are some key problems faced in modern agriculture that IoT-based smart farming. These problems such shortage of water, plant diseases, and pest attacks. Thus, artificial intelligence (AI) technology cooperates with the Internet of Things (IoT) ...

An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.

Scientific reports
The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features to predict meningioma grade. Three hundred forty meningiomas from one hospital composed the training set, and 102 meningiomas fr...

Detection of sugar beet seed coating defects via deep learning.

Scientific reports
The global seed coating market is expected to experience substantial growth, increasing from a 2023 valuation of USD 2.0 billion to an estimated value of USD 3.1 billion by 2028. This growth surge is primarily due to the consistent introduction of in...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Scientific reports
Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disorders early is essential for effective treatment, which traditionally relies on polysomnogram (PSG) t...