AIMC Topic: Algorithms

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A practical model for the identification of congenital cataracts using machine learning.

EBioMedicine
BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood ...

Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach.

Medical & biological engineering & computing
Cardiologists can acquire important information related to patients' cardiac health using carotid artery stiffness, its lumen diameter (LD), and its carotid intima-media thickness (cIMT). The sonographers primarily concern about the location of the a...

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation.

BMC genomics
BACKGROUND: To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite being a crucial issue in machine learn...

A Convolutional Neural Network for Real Time Classification, Identification, and Labelling of Vocal Cord and Tracheal Using Laryngoscopy and Bronchoscopy Video.

Journal of medical systems
BACKGROUND: The use of artificial intelligence, including machine learning, is increasing in medicine. Use of machine learning is rising in the prediction of patient outcomes. Machine learning may also be able to enhance and augment anesthesia clinic...

Learning efficient haptic shape exploration with a rigid tactile sensor array.

PloS one
Haptic exploration is a key skill for both robots and humans to discriminate and handle unknown objects or to recognize familiar objects. Its active nature is evident in humans who from early on reliably acquire sophisticated sensory-motor capabiliti...

A new deep learning method for image deblurring in optical microscopic systems.

Journal of biophotonics
Deconvolution is the most commonly used image processing method in optical imaging systems to remove the blur caused by the point-spread function (PSF). While this method has been successful in deblurring, it suffers from several disadvantages, such ...

A new backpropagation neural network classification model for prediction of incidence of malaria.

Frontiers in bioscience (Landmark edition)
Malaria is an infectious disease caused by parasitic protozoans of the Plasmodium family. These parasites are transmitted by mosquitos which are common in certain parts of the world. Based on their specific climates, these regions have been classifie...

A Multimodal Wearable System for Continuous and Real-Time Breathing Pattern Monitoring During Daily Activity.

IEEE journal of biomedical and health informatics
OBJECTIVE: This study aims to understand breathing patterns during daily activities by developing a wearable respiratory and activity monitoring (WRAM) system.

Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research.

Journal of biomedical informatics
OBJECTIVE: The speed of the diagnosis process is vital in pursuing the trial of curing cancer. During the last decade, precision medicine evolved by detecting different types of cancer through microarrays (MA) of deoxyribonucleic acid (DNA) processed...

Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction.

Health informatics journal
In order to evaluate mortality predictions based on boosted trees, this retrospective study uses electronic medical record data from three academic health centers for inpatients 18 years or older with at least one observation of each vital sign. Pred...