AIMC Topic: Area Under Curve

Clear Filters Showing 201 to 210 of 1194 articles

NeuroPpred-SVM: A New Model for Predicting Neuropeptides Based on Embeddings of BERT.

Journal of proteome research
Neuropeptides play pivotal roles in different physiological processes and are related to different kinds of diseases. Identification of neuropeptides is of great benefit for studying the mechanism of these physiological processes and the treatment of...

DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence.

Cell reports. Medicine
Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-worl...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Scientific reports
Bioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensi...

Machine-learning-based ground sink susceptibility evaluation using underground pipeline data in Korean urban area.

Scientific reports
Ground subsidence caused by natural factors, including groundwater, has been extensively researched. However, there have been few studies on ground sink caused mainly by artifacts, including underground pipelines in urban areas. This paper proposes a...

Mortality prediction in ICU Using a Stacked Ensemble Model.

Computational and mathematical methods in medicine
Artificial intelligence (AI) technology has huge scope in developing models to predict the survival rate of critically ill patients in the intensive care unit (ICU). The availability of electronic clinical data has led to the widespread use of variou...

Preoperative prediction of lymph node status in patients with colorectal cancer. Developing a predictive model using machine learning.

International journal of colorectal disease
PURPOSE: Develop a prediction model to determine the probability of no lymph node metastasis (pN0) in patients with colorectal cancer.

Deep multiple instance learning for predicting chemotherapy response in non-small cell lung cancer using pretreatment CT images.

Scientific reports
The individual prognosis of chemotherapy is quite different in non-small cell lung cancer (NSCLC). There is an urgent need to precisely predict and assess the treatment response. To develop a deep multiple-instance learning (DMIL) based model for pre...

Detection of mandibular fractures on panoramic radiographs using deep learning.

Scientific reports
Mandibular fractures are among the most frequent facial traumas in oral and maxillofacial surgery, accounting for 57% of cases. An accurate diagnosis and appropriate treatment plan are vital in achieving optimal re-establishment of occlusion, functio...

Diagnostic performance of artificial intelligence in multiple sclerosis: a systematic review and meta-analysis.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: The expansion of the availability of advanced imaging methods needs more time, expertise, and resources which is in contrast to the primary goal of the imaging techniques. To overcome most of these difficulties, artificial intelligence (A...

A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning.

BMC bioinformatics
BACKGROUND: Selecting and prioritizing candidate disease genes is necessary before conducting laboratory studies as identifying disease genes from a large number of candidate genes using laboratory methods, is a very costly and time-consuming task. T...