AIMC Topic: Algorithms

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Empirical mode decomposition in clinical signal analysis: A systematic review.

Computers in biology and medicine
This systematic review examines the transformative applications of empirical mode decomposition (EMD) in healthcare, focusing on its ability to analyse diverse physiological signals. By a thorough exploration of key databases and stringent study sele...

A multi-phase approach using supervised algorithms and clinical models to generate high-accuracy signatures for pancreatic cancer.

Computers in biology and medicine
BACKGROUND: The in silico analyses provide evidence supporting the potential of methylation-driven differentially expressed genes as therapeutic targets across cancer types. This leads us to identify novel targets and their associated drug compounds ...

Predicting time to live birth with deep learning embryo ranking: a novel multiple imputation approach.

Human reproduction (Oxford, England)
STUDY QUESTION: What is the clinical utility of embryo selection algorithms in estimating the time to live birth (TTLB)?

Accelerating Diffusion: Task-Optimized latent diffusion models for rapid CT denoising.

Computers in biology and medicine
Computed tomography (CT) systems are indispensable for diagnostics but pose risks due to radiation exposure. Low-dose CT (LDCT) mitigates these risks but introduces noise and artifacts that compromise diagnostic accuracy. While deep learning methods,...

A hybrid approach for machine learning based beat classification of ECG using different digital differentiators and DTCWT.

Computers in biology and medicine
This research paper presents a systematic approach to ECG beat classification using advanced machine learning techniques. The study classifies ECG beats into six distinct classes based on annotations from the MIT-BIH Arrhythmia Database. The methodol...

A nanozyme colorimetric sensor combined with cloud-based machine learning algorithm-assisted WeChat mini program for intelligent identification of Chinese green tea.

Food research international (Ottawa, Ont.)
Green tea has become increasingly renowned among consumers by virtue of its exceptional flavor and high nutritional value. There is often a strong correlation between the varieties of green tea, quality and corresponding price. In this work, a simple...

Ensemble learning approach for detecting breast invasive ductal carcinoma from histopathological images.

Pathology, research and practice
Invasive ductal carcinoma is a type of breast cancer that is one of the most frequent and aggressive forms of breast malignancy, necessitating accurate and timely diagnosis for effective treatment. Though considered the gold standard, traditional his...

Efficient few-shot medical image segmentation via self-supervised variational autoencoder.

Medical image analysis
Few-shot medical image segmentation typically uses a joint model for registration and segmentation. The registration model aligns a labeled atlas with unlabeled images to form initial masks, which are then refined by the segmentation model. However, ...

Learning contrast and content representations for synthesizing magnetic resonance image of arbitrary contrast.

Medical image analysis
Magnetic Resonance Imaging (MRI) produces images with different contrasts, providing complementary information for clinical diagnoses and research. However, acquiring a complete set of MRI sequences can be challenging due to limitations such as lengt...

Predicting metabolite-disease associations based on dynamic adaptive feature learning architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, the association between metabolites and complex human diseases has increasingly been recognized as a major research focus. Traditional wet-lab experiments are considered time-consuming and labor-intensive, w...