AIMC Topic: Algorithms

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An active learning approach for clustering single-cell RNA-seq data.

Laboratory investigation; a journal of technical methods and pathology
Single-cell RNA sequencing (scRNA-seq) data has been widely used to profile cellular heterogeneities with a high-resolution picture. Clustering analysis is a crucial step of scRNA-seq data analysis because it provides a chance to identify and uncover...

The application of feature engineering in establishing a rapid and robust model for identifying patients with glioma.

Lasers in medical science
The aim of the study is to evaluate the efficacy of the combination of Raman spectroscopy with feature engineering and machine learning algorithms for detecting glioma patients. In this study, we used Raman spectroscopy technology to collect serum sp...

Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.

Molecular diversity
Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can le...

Efficient Source Camera Identification with Diversity-Enhanced Patch Selection and Deep Residual Prediction.

Sensors (Basel, Switzerland)
Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed based on studying the traces left upon shooting, several deep-learning-based methods have also emerg...

Aggregation-and-Attention Network for brain tumor segmentation.

BMC medical imaging
BACKGROUND: Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted d...

Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.

PloS one
In current clinical settings, typically pain is measured by a patient's self-reported information. This subjective pain assessment results in suboptimal treatment plans, over-prescription of opioids, and drug-seeking behavior among patients. In the p...

A semi-analytical solution and AI-based reconstruction algorithms for magnetic particle tracking.

PloS one
Magnetic particle tracking is a recently developed technology that can measure the translation and rotation of a particle in an opaque environment like a turbidity flow and fluidized-bed flow. The trajectory reconstruction usually relies on numerical...

Fine-grained classification based on multi-scale pyramid convolution networks.

PloS one
The large intra-class variance and small inter-class variance are the key factor affecting fine-grained image classification. Recently, some algorithms have been more accurate and efficient. However, these methods ignore the multi-scale information o...

I Understand You: Blind 3D Human Attention Inference From the Perspective of Third-Person.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Inferring object-wise human attention in 3D space from the third-person perspective (e.g., a camera) is crucial to many visual tasks and applications, including human-robot collaboration, unmanned vehicle driving, etc. Challenges arise from classical...

Deep learning for peptide identification from metaproteomics datasets.

Journal of proteomics
Metaproteomics is becoming widely used in microbiome research for gaining insights into the functional state of the microbial community. Current metaproteomics studies are generally based on high-throughput tandem mass spectrometry (MS/MS) coupled wi...