AIMC Topic: Aged

Clear Filters Showing 8561 to 8570 of 14227 articles

[Gerontology, geriatric medicine and robot research : Look back to the future].

Zeitschrift fur Gerontologie und Geriatrie
Assistive robotics as a gerontological geriatric field of research so far seem to be perceived more as "recalcitrant". Predominant is a reserved attitude as to whether this should be considered a research topic to be taken seriously. The reliability ...

The Role of Mobility Digital Ecosystems for Age-Friendly Urban Public Transport: A Narrative Literature Review.

International journal of environmental research and public health
Within the context of the intersection of the global megatrends of urbanisation, ageing societies and digitalisation, this paper explores older people's mobility, with a particular interest in public transport, and a strong consideration of digital/I...

Temporary pacemaker insertion for severe bradycardia following pneumoperitoneum during robot-assisted radical prostatectomy: a case report.

BMC surgery
BACKGROUND: Pneumoperitoneum to maintain a constant gas flow to assist various surgeries is known to cause severe bradycardia and has been linked to heart failure;; however, a recent study demonstrated that it is not linked to poorer surgical outcome...

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...

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...

Machine Learning Improves the Identification of Individuals With Higher Morbidity and Avoidable Health Costs After Acute Coronary Syndromes.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Traditional risk scores improved the definition of the initial therapeutic strategy in acute coronary syndrome (ACS), but they were not designed for predicting long-term individual risks and costs. In parallel, attempts to directly predic...

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...