AIMC Topic: Middle Aged

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Application of an Artificial Intelligence Trilogy to Accelerate Processing of Suspected Patients With SARS-CoV-2 at a Smart Quarantine Station: Observational Study.

Journal of medical Internet research
BACKGROUND: As the COVID-19 epidemic increases in severity, the burden of quarantine stations outside emergency departments (EDs) at hospitals is increasing daily. To address the high screening workload at quarantine stations, all staff members with ...

Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The electronic medical record contains a wealth of information buried in free text. We created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone.

The Challenges of Implementing Artificial Intelligence into Surgical Practice.

World journal of surgery
BACKGROUND: Artificial intelligence is touted as the future of medicine. Classical algorithms for the detection of common bile duct stones (CBD) have had poor clinical uptake due to low accuracy. This study explores the challenges of developing and i...

Early Feasibility of Automated Artificial Intelligence Angiography Based Fractional Flow Reserve Estimation.

The American journal of cardiology
Despite the evidence of improved patients' outcome, fractional flow reserve (FFR) is underused in current everyday practice. We aimed to evaluate the feasibility of a novel automated artificial intelligence angiography-based FFR software (AutocathFFR...

A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre.

Nature biomedical engineering
Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here, we report the development and validation of deep-learning models for the automated measurement of retinal-vessel calibre in retinal photographs, using divers...

Clinical and laboratory data, radiological structured report findings and quantitative evaluation of lung involvement on baseline chest CT in COVID-19 patients to predict prognosis.

La Radiologia medica
OBJECTIVE: To evaluate by means of regression models the relationships between baseline clinical and laboratory data and lung involvement on baseline chest CT and to quantify the thoracic disease using an artificial intelligence tool and a visual sco...

Deep neural network based artificial intelligence assisted diagnosis of bone scintigraphy for cancer bone metastasis.

Scientific reports
Bone scintigraphy (BS) is one of the most frequently utilized diagnostic techniques in detecting cancer bone metastasis, and it occupies an enormous workload for nuclear medicine physicians. So, we aimed to architecture an automatic image interpretin...

Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer.

Scientific reports
Patients with pancreatic cancer have a poor prognosis, therefore identifying particular tumor characteristics associated with prognosis is important. This study aims to investigate the utility of radiomics with machine learning using F-fluorodeoxyglu...

Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease.

Circulation. Cardiovascular interventions
BACKGROUND: Peripheral artery disease (PAD) is underrecognized, undertreated, and understudied: each of these endeavors requires efficient and accurate identification of patients with PAD. Currently, PAD patient identification relies on diagnosis/pro...