AIMC Topic: Aged, 80 and over

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Unbiased identification of risk factors for invasive Escherichia coli disease using machine learning.

BMC infectious diseases
BACKGROUND: Invasive Escherichia coli disease (IED), also known as invasive extraintestinal pathogenic E. coli disease, is a leading cause of sepsis and bacteremia in older adults that can result in hospitalization and sometimes death and is frequent...

Measurable residual disease (MRD) dynamics in multiple myeloma and the influence of clonal diversity analyzed by artificial intelligence.

Blood cancer journal
Minimal residual disease (MRD) assessment is a known surrogate marker for survival in multiple myeloma (MM). Here, we present a single institution's experience assessing MRD by NGS of Ig genes and the long-term impact of depth of response as well as ...

Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.

Journal of applied gerontology : the official journal of the Southern Gerontological Society
This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...

Artificial intelligence prediction of In-Hospital mortality in patients with dementia: A multi-center study.

International journal of medical informatics
BACKGROUND: Prediction of mortality is very important for care planning in hospitalized patients with dementia and artificial intelligence has the potential to serve as a solution; however, this issue remains unclear. Thus, this study was conducted t...

Ensemble machine learning to predict futile recanalization after mechanical thrombectomy based on non-contrast CT imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Despite successful recanalization after Mechanical Thrombectomy (MT), approximately 25 % of patients with Acute Ischemic Stroke (AIS) due to Large Vessel Occlusion (LVO) show unfavorable clinical outcomes, namely Futile Recanalization (FR...

Integrating Deep Learning-Based Dose Distribution Prediction with Bayesian Networks for Decision Support in Radiotherapy for Upper Gastrointestinal Cancer.

Cancer research and treatment
PURPOSE: Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) or magnetic resonance-guided gated delivery using MRIdian (MRG), is time-consuming and costly. To add...

Botulinum Toxin Type A (BoNT-A) Use for Post-Stroke Spasticity: A Multicenter Study Using Natural Language Processing and Machine Learning.

Toxins
We conducted a multicenter and retrospective study to describe the use of botulinum toxin type A (BoNT-A) to treat post-stroke spasticity (PSS). Data were extracted from free-text in electronic health records (EHRs) in five Spanish hospitals. We incl...

Machine learning in diagnostic support in medical emergency departments.

Scientific reports
Diagnosing patients in the medical emergency department is complex and this is expected to increase in many countries due to an ageing population. In this study we investigate the feasibility of training machine learning algorithms to assist physicia...

Deep learning predicts the 1-year prognosis of pancreatic cancer patients using positive peritoneal washing cytology.

Scientific reports
Peritoneal washing cytology (CY) in patients with pancreatic cancer is mainly used for staging; however, it may also be used to evaluate the intraperitoneal status to predict a more accurate prognosis. Here, we investigated the potential of deep lear...