AIMC Topic: Deep Learning

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X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.

Computers in biology and medicine
In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifying differences between lineages are crucial for understanding cell differentiation processes and reducing early pregnancy miscarriages in humans. This...

Gabor-modulated depth separable convolution for retinal vessel segmentation in fundus images.

Computers in biology and medicine
BACKGROUND: In diabetic retinopathy, precise segmentation of retinal vessels is essential for accurate diagnosis and effective disease management. This task is particularly challenging due to the varying sizes of vessels, their bifurcations, and the ...

Multitask learning approach for PPG applications: Case studies on signal quality assessment and physiological parameters estimation.

Computers in biology and medicine
Wearable technology has expanded the applications of photoplethysmography (PPG) in remote health monitoring, enabling real-time measurement of various physiological parameters, such as heart rate (HR), heart rate variability (HRV), and respiration ra...

Deep Learning-Assisted Discovery of Protein Entangling Motifs.

Biomacromolecules
Natural topological proteins exhibit unique properties including enhanced stability, controlled quaternary structures, and dynamic switching properties, highlighting topology as a unique dimension in protein engineering. Although artificial design an...

Deep learning-based prediction of possibility for immediate implant placement using panoramic radiography.

Scientific reports
In this study, we investigated whether deep learning-based prediction of immediate implant placement is possible. Panoramic radiographs of 201 patients with 874 teeth (Group 1: 440 teeth difficult to place implant immediately after extraction, Group ...

Learning based lower limb joint kinematic estimation using open source IMU data.

Scientific reports
This study introduces a deep learning framework for estimating lower-limb joint kinematics using inertial measurement units (IMUs). While deep learning methods avoid sensor drift, extensive calibration, and complex setup procedures, they require subs...

Automated grading of oleaster fruit using deep learning.

Scientific reports
The agriculture sector is crucial to many economies, particularly in developing regions, with post-harvest technology emerging as a key growth area. The oleaster, valued for its nutritional and medicinal properties, has traditionally been graded manu...

Deep learning-based quick MLC sequencing for MRI-guided online adaptive radiotherapy: a feasibility study for pancreatic cancer patients.

Physics in medicine and biology
One bottleneck of magnetic resonance imaging (MRI)-guided online adaptive radiotherapy is the time-consuming daily online replanning process. The current leaf sequencing method takes up to 10 min, with potential dosimetric degradation and small segme...

Advances of deep Neural Networks (DNNs) in the development of peptide drugs.

Future medicinal chemistry
Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexi...

A novel deep learning-based framework with particle swarm optimisation for intrusion detection in computer networks.

PloS one
Intrusion detection plays a significant role in the provision of information security. The most critical element is the ability to precisely identify different types of intrusions into the network. However, the detection of intrusions poses a importa...