AIMC Topic: Middle Aged

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Relevance of Complaint Severity in Predicting the Progression of Subjective Cognitive Decline and Mild Cognitive Impairment: A Machine Learning Approach.

Journal of Alzheimer's disease : JAD
BACKGROUND: The presence of subjective cognitive complaints (SCCs) is a core criterion for diagnosis of subjective cognitive decline (SCD); however, no standard procedure for distinguishing normative and non-normative SCCs has yet been established.

Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Technology in cancer research & treatment
Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinical behaviors of the two tumor types. We propose the use of a deep learning and transfer learning appr...

Prediction of Radiation Pneumonitis With Machine Learning in Stage III Lung Cancer: A Pilot Study.

Technology in cancer research & treatment
BACKGROUND: Radiation pneumonitis (RP) is a dose-limiting toxicity in lung cancer radiotherapy (RT). As risk factors in the development of RP, patient and tumor characteristics, dosimetric parameters, and treatment features are intertwined, and it is...

Cost-Effective Machine Learning Based Clinical Pre-Test Probability Strategy for DVT Diagnosis in Neurological Intensive Care Unit.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
In order to overcome the shortage of the current costly DVT diagnosis and reduce the waste of valuable healthcare resources, we proposed a new diagnostic approach based on machine learning pre-test prediction models using EHRs. We examined the sociod...

Natural Language Processing Performance for the Identification of Venous Thromboembolism in an Integrated Healthcare System.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Real-time identification of venous thromboembolism (VTE), defined as deep vein thrombosis (DVT) and pulmonary embolism (PE), can inform a healthcare organization's understanding of these events and be used to improve care. In a former publication, we...

Effect of robotic exoskeleton gait training during acute stroke on functional ambulation.

NeuroRehabilitation
BACKGROUND: Stroke is a leading cause of disability resulting in long-term functional ambulation deficits. Conventional therapy can improve ambulation, but may not be able to provide consistent, high dose repetition of movement, resulting in variable...

Screening for Early-Stage Alzheimer's Disease Using Optimized Feature Sets and Machine Learning.

Journal of Alzheimer's disease : JAD
BACKGROUND: Detecting early-stage Alzheimer's disease in clinical practice is difficult due to a lack of efficient and easily administered cognitive assessments that are sensitive to very mild impairment, a likely contributor to the high rate of unde...

Referral for disease-related visual impairment using retinal photograph-based deep learning: a proof-of-concept, model development study.

The Lancet. Digital health
BACKGROUND: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to eye diseases. The emergence of dee...

Temporal changes of quantitative CT findings from 102 patients with COVID-19 in Wuhan, China: A longitudinal study.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Computed tomography (CT) imaging combined with artificial intelligence is important in the diagnosis and prognosis of lung diseases.