AIMC Topic: Databases, Factual

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Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach.

BMC medical informatics and decision making
BACKGROUND: A common problem in machine learning applications is availability of data at the point of decision making. The aim of the present study was to use routine data readily available at admission to predict aspects relevant to the organization...

Deep learning for prediction of cardiac indices from photoplethysmographic waveform: A virtual database approach.

International journal for numerical methods in biomedical engineering
Deep learning methods combined with large datasets have recently shown significant progress in solving several medical tasks. However, collecting and annotating large datasets can be a very cumbersome and expensive task. We tackle these problems with...

Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone.

BMC medical informatics and decision making
BACKGROUND: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enough blood to meet the needs of...

User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Precision cancer medicine is dependent on accurate prediction of disease and treatment outcome, requiring integration of clinical, imaging and interventional knowledge. User controlled pipelines are capable of feature integration with varied...

Towards Domain Invariant Heart Sound Abnormality Detection Using Learnable Filterbanks.

IEEE journal of biomedical and health informatics
OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for the early diagnosis of heart diseases. While machine learning based systems can aid in automatically screening patients, the robustness of these syste...

Deep Neural Networks for Chronological Age Estimation From OPG Images.

IEEE transactions on medical imaging
Chronological age estimation is crucial labour in many clinical procedures, where the teeth have proven to be one of the best estimators. Although some methods to estimate the age from tooth measurements in orthopantomogram (OPG) images have been dev...

Computer-aided diagnosis of breast ultrasound images using ensemble learning from convolutional neural networks.

Computer methods and programs in biomedicine
Breast ultrasound and computer aided diagnosis (CAD) has been used to classify tumors into benignancy or malignancy. However, conventional CAD software has some problems (such as handcrafted features are hard to design; conventional CAD systems are d...

Deep pancreas segmentation with uncertain regions of shadowed sets.

Magnetic resonance imaging
Pancreas segmentation is a challenging task in medical image analysis especially for the patients with pancreatic cancer. First, the images often have poor contrast and blurred boundaries. Second, there exist large variations in gray scale, texture, ...

Research of Multimodal Medical Image Fusion Based on Parameter-Adaptive Pulse-Coupled Neural Network and Convolutional Sparse Representation.

Computational and mathematical methods in medicine
Visual effects of medical image have a great impact on clinical assistant diagnosis. At present, medical image fusion has become a powerful means of clinical application. The traditional medical image fusion methods have the problem of poor fusion re...

Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

PloS one
OBJECTIVE: To assess the classification performance between Parkinson's disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT...