AIMC Topic: Artificial Intelligence

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Predictive value of a novel Asian lung cancer screening nomogram based on artificial intelligence and epidemiological characteristics.

Thoracic cancer
BACKGROUND: To develop and validate a risk prediction nomogram based on a deep learning convolutional neural networks (CNN) model and epidemiological characteristics for lung cancer screening in patients with small pulmonary nodules (SPN).

Projections of IoT Applications in Colombia Using 5G Wireless Networks.

Sensors (Basel, Switzerland)
Wireless technologies are increasingly relevant in different activities and lines of the economy, as well as in the daily life of people and companies. The advent of fifth generation networks (5G) implies a promising synergy with the Internet of Thin...

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

International journal of environmental research and public health
Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diag...

Segmentation of vestibular schwannoma from MRI, an open annotated dataset and baseline algorithm.

Scientific data
Automatic segmentation of vestibular schwannomas (VS) from magnetic resonance imaging (MRI) could significantly improve clinical workflow and assist patient management. We have previously developed a novel artificial intelligence framework based on a...

Applying deep learning to quantify empty lacunae in histologic sections of osteonecrosis of the femoral head.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Osteonecrosis of the femoral head (ONFH) is a disease in which inadequate blood supply to the subchondral bone causes the death of cells in the bone marrow. Decalcified histology and assessment of the percentage of empty lacunae are used to quantify ...

Knowledge-based approaches to drug discovery for rare diseases.

Drug discovery today
The conventional drug discovery pipeline has proven to be unsustainable for rare diseases. Herein, we discuss recent advances in biomedical knowledge mining applied to discovering therapeutics for rare diseases. We summarize current chemogenomics dat...

AiED: Artificial intelligence for the detection of intracranial interictal epileptiform discharges.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Deep learning provides an appealing solution for the ongoing challenge of automatically classifying intracranial interictal epileptiform discharges (IEDs). We report results from an automated method consisting of a template-matching algori...

Current applications of artificial intelligence in vascular surgery.

Seminars in vascular surgery
Basic foundations of artificial intelligence (AI) include analyzing large amounts of data, recognizing patterns, and predicting outcomes. At the core of AI are well-defined areas, such as machine learning, natural language processing, artificial neur...

Artificial intelligence's role in vascular surgery decision-making.

Seminars in vascular surgery
Artificial intelligence (AI) is the next great advance informing medical science. Several disciplines, including vascular surgery, use AI-based decision-making tools to improve clinical performance. Although applied widely, AI functions best when con...

Review and current update of robotic-assisted laparoscopic vascular surgery.

Seminars in vascular surgery
The field of vascular surgery is constantly evolving and is unsurpassed in its innovation and adoption of new technologies. Endovascular therapy has fundamentally changed the treatment paradigms for aneurysm and occlusive disease. As we continue to m...