AIMC Topic: Deep Learning

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Integrating radiomics and gene expression by mapping on the image with improved DeepInsight for clear cell renal cell carcinoma.

Cancer genetics Feb 14, 2025
BACKGROUND: Radiomics analysis extracts high-dimensional features from medical images, which are used to predict outcomes in machine learning (ML). Recently, deep-learning methods have become applicable to image data converted from nonimage samples.
Neural Networks, Computer Machine Learning Kidney Neoplasms Algorithms Carcinoma, Renal Cell Humans Gene Expression Profiling Deep Learning Aged Image Processing, Computer-Assisted Radiomics Male Middle Aged Prognosis Tomography, X-Ray Computed Female
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Finger-aware Artificial Neural Network for predicting arthritis in Patients with hand pain.

Artificial intelligence in medicine Feb 14, 2025
Arthritis is an inflammatory condition associated with joint damage, the incidence of which is increasing worldwide. In severe cases, arthritis can result in the restriction of joint movement, thereby affecting daily activities; as such, early and ac...
Neural Networks, Computer Machine Learning Algorithms Adult Male Female Aged Humans Hand Pain Middle Aged Deep Learning Fingers ROC Curve Arthritis
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A-Eval: A benchmark for cross-dataset and cross-modality evaluation of abdominal multi-organ segmentation.

Medical image analysis Feb 14, 2025
Although deep learning has revolutionized abdominal multi-organ segmentation, its models often struggle with generalization due to training on small-scale, specific datasets and modalities. The recent emergence of large-scale datasets may mitigate th...
Humans Tomography, X-Ray Computed Benchmarking Deep Learning Abdomen Magnetic Resonance Imaging
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PBScreen: A server for the high-throughput screening of placental barrier-permeable contaminants based on multifusion deep learning.

Environmental pollution (Barking, Essex : 1987) Feb 14, 2025
Contaminants capable of crossing the placental barrier (PB) adversely affect female reproduction and fetal development. The rapid identification of PB-permeable contaminants is urgently needed due to the inefficiencies of conventional cell-based tran...
Placenta Environmental Pollutants High-Throughput Screening Assays Pregnancy Humans Female Deep Learning
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A deep-learning model for predicting tyrosine kinase inhibitor response from histology in gastrointestinal stromal tumor.

The Journal of pathology Feb 14, 2025
Over 90% of gastrointestinal stromal tumors (GISTs) harbor mutations in KIT or PDGFRA that can predict response to tyrosine kinase inhibitor (TKI) therapies, as recommended by NCCN (National Comprehensive Cancer Network) guidelines. However, gene seq...
Mutation Gastrointestinal Neoplasms Gastrointestinal Stromal Tumors Imatinib Mesylate Middle Aged Deep Learning Treatment Outcome Triazines Proto-Oncogene Proteins c-kit Aged Tyrosine Kinase Inhibitors Pyrazoles Male Receptor, Platelet-Derived Growth Factor alpha Humans Protein Kinase Inhibitors Female Pyrroles
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Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring.

ACS applied materials & interfaces Feb 14, 2025
Prolonged use of digital devices and sedentary lifestyles have led to an increase in the prevalence of cervical spondylosis among young people, highlighting the urgent need for preventive measures. Recent advancements in triboelectric nanogenerators ...
Humans Neck Monitoring, Physiologic Hydrogels Glycerol Algorithms Polyvinyl Alcohol Deep Learning Movement Wearable Electronic Devices
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Data Reconstruction Methods in Multi-Feature Fusion CNN Model for Enhanced Human Activity Recognition.

Sensors (Basel, Switzerland) Feb 14, 2025
BACKGROUND: Human activity recognition (HAR) plays a pivotal role in digital healthcare, enabling applications such as exercise monitoring and elderly care. However, traditional HAR methods relying on accelerometer data often require complex preproce...
Deep Learning Humans Accelerometry Neural Networks, Computer Human Activities Algorithms
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Exploring Potential Medications for Alzheimer's Disease with Psychosis by Integrating Drug Target Information into Deep Learning Models: A Data-Driven Approach.

International journal of molecular sciences Feb 14, 2025
Approximately 50% of Alzheimer's disease (AD) patients develop psychotic symptoms, leading to a subtype known as psychosis in AD (AD + P), which is associated with accelerated cognitive decline compared to AD without psychosis. Currently, no FDA-appr...
Alzheimer Disease Humans Antipsychotic Agents Electronic Health Records Aged Deep Learning Female Male Psychotic Disorders
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Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network.

Journal of orthopaedic surgery and research Feb 14, 2025
BACKGROUND: Traditional diagnostic tools for scoliosis screening necessitate a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We h...
Back Child Mass Screening Scoliosis Humans Neural Networks, Computer Female Convolutional Neural Networks Adolescent Male Deep Learning
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Reducing inference cost of Alzheimer's disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners.

Scientific reports Feb 14, 2025
While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG PET) data have shown promise in the accurate identification of Alzheimer's disease, their clinical appl...
Humans Brain Positron-Emission Tomography Fluorodeoxyglucose F18 Uncertainty Deep Learning Magnetic Resonance Imaging Alzheimer Disease
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