AIMC Topic: Aged
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Explaining deep learning models for age-related gait classification based on acceleration time series.
Computers in biology and medicine
Nov 12, 2024
BACKGROUND: Gait analysis holds significant importance in monitoring daily health, particularly among older adults. Advancements in sensor technology enable the capture of movement in real-life environments and generate big data. Machine learning, no...
Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.
Genes
Nov 12, 2024
Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. The anoikis-related prognostic signature (ANRS) was gene...
Treatment Outcome
Databases, Genetic
Predictive Value of Tests
Drug Screening Assays, Antitumor
Gene Expression
Prognosis
Blotting, Western
Female
Imatinib Mesylate
Reproducibility of Results
Proportional Hazards Models
Aged
Anoikis
Breast Neoplasms
Machine Learning
Transcriptome
Tumor Microenvironment
Real-Time Polymerase Chain Reaction
Biomarkers, Tumor
Reverse Transcriptase Polymerase Chain Reaction
Middle Aged
Immunotherapy
Antineoplastic Agents
Enzyme-Linked Immunosorbent Assay
Gene Expression Profiling
A F-FDG PET/CT-based deep learning-radiomics-clinical model for prediction of cervical lymph node metastasis in esophageal squamous cell carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Nov 12, 2024
BACKGROUND: To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (DL) features extracted from F-fluorodeoxyglucose (F-FDG) Positron emission tomography/Computed Tomography (PET/CT) images of tumor and cervical lymph n...
Factors and machine learning models for predicting successful discontinuation of continuous renal replacement therapy in critically ill patients with acute kidney injury: a retrospective cohort study based on MIMIC-IV database.
BMC nephrology
Nov 12, 2024
BACKGROUND: For critically ill patients with acute kidney injury (AKI), there remains controversy regarding the predictive factors affecting the discontinuation of continuous renal replacement therapy (CRRT). This study aims to explore factors associ...
A comparative study to elucidate factors explaining willingness to use home-care robots in Japan, Ireland, and Finland.
Scientific reports
Nov 12, 2024
The implementation of home-care robots is sometimes unsuccessful. This study aimed to explore factors explaining people's willingness to use home-care robots, particularly among care recipients and caregivers. Surveys were conducted in Japan, Ireland...
SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer.
Scientific reports
Nov 12, 2024
Fluorouracil-based chemotherapy responses in colorectal cancer (CRC) patients vary widely, highlighting the role of pharmacogenomics in developing better predictive models. We analyzed 379 CRC patients receiving fluorouracil-based chemotherapy, colle...
A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers.
BMC medical imaging
Nov 12, 2024
BACKGROUND: Speckle tracking echocardiography (STE) provides quantification of left ventricular (LV) deformation and is useful in the assessment of LV function. STE is increasingly being used clinically, and every effort to simplify and standardize S...
The established of a machine learning model for predicting the efficacy of adjuvant interferon alpha1b in patients with advanced melanoma.
Frontiers in immunology
Nov 12, 2024
BACKGROUND: Interferon-alpha1b (IFN-α1b) has shown remarkable therapeutic potential as adjuvant therapy for melanoma. This study aimed to develop five machine learning models to evaluate the efficacy of postoperative IFN-α1b in patients with advanced...
High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique.
Japanese journal of radiology
Nov 11, 2024
PURPOSE: The purpose of this study was to investigate whether the high-precision magnetic resonance (MR) sequence using modified Fast 3D mode wheel and Precise IQ Engine (PIQE), that was collected in a wheel shape with sequential data filling in the ...
Exploring the potential of large language models in identifying metabolic dysfunction-associated steatotic liver disease: A comparative study of non-invasive tests and artificial intelligence-generated responses.
Liver international : official journal of the International Association for the Study of the Liver
Nov 11, 2024
BACKGROUND AND AIMS: This study sought to assess the capabilities of large language models (LLMs) in identifying clinically significant metabolic dysfunction-associated steatotic liver disease (MASLD).
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