Preventive Care

A Novel Internet of Things Framework Integrated with Real Time Monitoring for Intelligent Healthcare Environment.

During mammogram screening, there is a higher probability that detection of cancers is missed, and more than 16 percentage of breast cancer is not detected by radiologists. This problem can be solved by employing image processing algorithms which enhances the accuracy of the diagnostic through image segmentation which reduces the misclassified malignant cancers. By employing segmentation, the unne...

Deep Residual Inception Encoder-Decoder Network for Medical Imaging Synthesis.

Image synthesis is a novel solution in precision medicine for scenarios where important medical imaging is not otherwise available. The convolutional neural network (CNN) is an ideal model for this task because of its powerful learning capabilities through the large number of layers and trainable parameters. In this research, we propose a new architecture of residual inception encoder-decoder neur...

The use of natural language processing to identify Tdap-related local reactions at five health care systems in the Vaccine Safety Datalink.

OBJECTIVE: Local reactions are the most common vaccine-related adverse event. There is no specific diagnosis code for local reaction due to vaccinatio...

Improving Automatic Polyp Detection Using CNN by Exploiting Temporal Dependency in Colonoscopy Video.

Automatic polyp detection has been shown to be difficult due to various polyp-like structures in the colon and high interclass variations in polyp siz...

Quality assurance of computer-aided detection and diagnosis in colonoscopy.

Recent breakthroughs in artificial intelligence (AI), specifically via its emerging sub-field "deep learning," have direct implications for computer-a...

Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning.

Virtual screening is a promising method for obtaining novel hit compounds in drug discovery. It aims to enrich potentially active compounds from a lar...

Machine Learning Enhances the Efficiency of Cognitive Screenings for Primary Care.

BACKGROUND: Incorporation of cognitive screening into the busy primary care will require the development of highly efficient screening tools. We repor...

Estimation of echocardiogram parameters with the aid of impedance cardiography and artificial neural networks.

The advent of cardiovascular diseases as a disease of mass catastrophy, in recent years is alarming. It is expected to spread as an epidemic by 2030. ...

Addressing priority challenges in the detection and assessment of colorectal polyps from capsule endoscopy and colonoscopy in colorectal cancer screening using machine learning.

BACKGROUND: Colorectal capsule endoscopy (CCE) is a potentially valuable patient-friendly technique for colorectal cancer screening in large populatio...

Retinal blood vessel extraction employing effective image features and combination of supervised and unsupervised machine learning methods.

In medicine, retinal vessel analysis of fundus images is a prominent task for the screening and diagnosis of various ophthalmological and cardiovascul...

Artificial intelligence and colonoscopy: Current status and future perspectives.

BACKGROUND AND AIM: Application of artificial intelligence in medicine is now attracting substantial attention. In the field of gastrointestinal endos...

Automatic inference of BI-RADS final assessment categories from narrative mammography report findings.

We propose an efficient natural language processing approach for inferring the BI-RADS final assessment categories by analyzing only the mammogram fin...

Exploration of the nanomedicine-design space with high-throughput screening and machine learning.

Only a tiny fraction of the nanomedicine-design space has been explored, owing to the structural complexity of nanomedicines and the lack of relevant ...

Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.

BACKGROUND: Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening...

RAMS: Remote and automatic mammogram screening.

About one in eight women in the U.S. will develop invasive breast cancer at some point in life. Breast cancer is the most common cancer found in women...

Potential roles of artificial intelligence learning and faecal immunochemical testing for prioritisation of colonoscopy in anaemia.

Iron deficiency anaemia (IDA) is the most common cause of anaemia and a frequent indication for colonoscopy, although the prevalence of colorectal can...

Hepatitis Screening and Treatment Campaign in Malaysia-Validation of Low-cost Point of Care Screening Tests and Nucleic Acid Tests for Hepatitis B and C.

BACKGROUND: Two major challenges in implementing budget-constrained Hepatitis screening and treatment campaign in Malaysia are the availability of low...

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli.

The field of synthetic biology aims to make the design of biological systems predictable, shrinking the huge design space to practical numbers for tes...

Association of time to colonoscopy after a positive fecal test result and fecal hemoglobin concentration with risk of advanced colorectal neoplasia.

BACKGROUND: We evaluated the risk of advanced colorectal neoplasia (ACRN) and colorectal cancer (CRC) according to time to colonoscopy after positive ...

Multifunctional luminescent immuno-magnetic nanoparticles: toward fast, efficient, cell-friendly capture and recovery of circulating tumor cells.

Highly efficient isolation and recovery of viable circulating tumor cells (CTCs) from the blood of patients is an important precondition to address th...