AIMC Topic: Aged

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A robust automated segmentation method for white matter hyperintensity of vascular-origin.

NeuroImage
White matter hyperintensity (WMH) is a primary manifestation of small vessel disease (SVD), leading to vascular cognitive impairment and other disorders. Accurate WMH quantification is vital for diagnosis and prognosis, but current automatic segmenta...

Development and validation of a machine learning model based on complete blood counts to predict clinical outcomes in urothelial carcinoma patients.

Clinica chimica acta; international journal of clinical chemistry
Urothelial carcinoma (UC) is a highly malignant disease with significant public health implications. Despite advancements in oncology, early diagnosis and effective prognostic tools remain limited. This study aimed to develop a machine learning model...

A Transformer-Based Framework for Counterfactual Estimation of Antihypertensive Treatment Effect on COVID-19 Infection Risk - A Proof-of-Concept Study.

American journal of hypertension
BACKGROUND: Transformer-based neural networks excel in modelling high-dimensional, time-series data with complex dependencies. This proof-of-concept study applies a transformer-X-learner framework to estimate treatment effects using real-world data, ...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Nanoscale
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...

Novel composite health assessment risk model for older allogeneic transplant recipients: BMT-CTN 1704.

Blood advances
Allogeneic hematopoietic cell transplantation (allo-HCT) is potentially curative for older adults with hematologic malignancies. Concerns on nonrelapse mortality (NRM) in older adults limit allo-HCT utilization. We executed a prospective, observation...

Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning.

Brain : a journal of neurology
The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As demand for thrombectomy rises and geographical disparities in stroke...

Artificial intelligence models using F-wave responses predict amyotrophic lateral sclerosis.

Brain : a journal of neurology
Nerve conduction F-wave studies contain crucial information about subclinical motor dysfunction that can be used to diagnose patients with amyotrophic lateral sclerosis (ALS). However, F-wave responses are highly variable in morphology, making wavefo...

Protocol for a multicenter randomized controlled trial to assess the usefulness of computer-aided detection systems for colonoscopy in colorectal cancer screening in the Asia-Pacific region (project CAD/NCCH2217).

Japanese journal of clinical oncology
Ensuring the high quality of colonoscopies in colorectal cancer (CRC) screening is essential to reducing CRC. Recently, computer-aided detection systems (CADe) that use artificial intelligence have attracted much attention as potentially useful tools...

Deep learning on high-density EEG during a cognitive task distinguishes patients with Parkinson's disease from healthy controls.

Journal of neural engineering
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms, including cognitive impairment. Its diagnosis, which used to be based on clinical assessment, increasingly relies on biomarkers. While electroence...