AIMC Topic: Algorithms

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Evaluating spatially enabled machine learning approaches to depth to bedrock mapping, Alberta, Canada.

PloS one
Maps showing the thickness of sediments above the bedrock (depth to bedrock, or DTB) are important for many geoscience studies and are necessary for many hydrogeological, engineering, mining, and forestry applications. However, it can be difficult to...

A machine learning based depression screening framework using temporal domain features of the electroencephalography signals.

PloS one
Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely and precise recognition of depression is vital for appropriate mediation and effective treatment. Electroencephalography (EEG) has surfaced as a promis...

Automating sedation state assessments using natural language processing.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
INTRODUCTION: Common goals for procedural sedation are to control pain and ensure the patient is not moving to an extent that is impeding safe progress or completion of the procedure. Clinicians perform regular assessments of the adequacy of procedur...

Multi-center Dose Prediction Using Attention-aware Deep learning Algorithm Based on Transformers for Cervical Cancer Radiotherapy.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: Accurate dose delivery is crucial for cervical cancer volumetric modulated arc therapy (VMAT). We aimed to develop a robust deep-learning (DL) algorithm for fast and accurate dose prediction of cervical cancer VMAT in multicenter datasets and t...

A lightweight and gradient-stable neural layer.

Neural networks : the official journal of the International Neural Network Society
To enhance resource efficiency and model deployability of neural networks, we propose a neural-layer architecture based on Householder weighting and absolute-value activating, called Householder-absolute neural layer or simply Han-layer. Compared to ...

Deep local-to-global feature learning for medical image super-resolution.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical images play a vital role in medical analysis by providing crucial information about patients' pathological conditions. However, the quality of these images can be compromised by many factors, such as limited resolution of the instruments, art...

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
OBJECTIVES: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of ris...

The multimodality cell segmentation challenge: toward universal solutions.

Nature methods
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different exp...

Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.

Cardiovascular and interventional radiology
PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.

iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks.

Artificial intelligence in medicine
Globally, fungal infections have become a major health concern in humans. Fungal diseases generally occur due to the invading fungus appearing on a specific portion of the body and becoming hard for the human immune system to resist. The recent emerg...