AIMC Topic: Humans

Clear Filters Showing 27091 to 27100 of 95995 articles

An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this st...

ChatGPT as an "author": Bibliometric analysis to assess the validity of authorship.

Accountability in research
: Following the 2023 surge in popularity of large language models like ChatGPT, significant ethical discussions emerged regarding their role in academic authorship. Notable ethics organizations, including the ICMJE and COPE, alongside leading publish...

ECG-surv: A deep learning-based model to predict time to 1-year mortality from 12-lead electrocardiogram.

Biomedical journal
BACKGROUND: Electrocardiogram (ECG) abnormalities have demonstrated potential as prognostic indicators of patient survival. However, the traditional statistical approach is constrained by structured data input, limiting its ability to fully leverage ...

Preoperative CECT-Based Multitask Model Predicts Peritoneal Recurrence and Disease-Free Survival in Advanced Ovarian Cancer: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: Peritoneal recurrence is the predominant pattern of recurrence in advanced ovarian cancer (AOC) and portends a dismal prognosis. Accurate prediction of peritoneal recurrence and disease-free survival (DFS) is crucial to iden...

Deep Learning Synthesis of White-Blood From Dark-Blood Late Gadolinium Enhancement Cardiac Magnetic Resonance.

Investigative radiology
OBJECTIVES: Dark-blood late gadolinium enhancement (DB-LGE) cardiac magnetic resonance has been proposed as an alternative to standard white-blood LGE (WB-LGE) imaging protocols to enhance scar-to-blood contrast without compromising scar-to-myocardiu...

Predicting Osteoporosis and Osteopenia by Fusing Deep Transfer Learning Features and Classical Radiomics Features Based on Single-Source Dual-energy CT Imaging.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a predictive model for osteoporosis and osteopenia prediction by fusing deep transfer learning (DTL) features and classical radiomics features based on single-source dual-energy computed tomography (C...

The relationship between satisfaction with life, dietary attitude, and comfort level in hemodialysis patients: Analysis with machine learning approach.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy
INTRODUCTION: Hemodialysis (HD) patients have become a serious public health problem, the number of which is increasing every year worldwide. This study aimed to determine the relationship between satisfaction with life, dietary attitude, and comfort...

Deep learning in magnetic resonance enterography for Crohn's disease assessment: a systematic review.

Abdominal radiology (New York)
Crohn's disease (CD) poses significant morbidity, underscoring the need for effective, non-invasive inflammatory assessment using magnetic resonance enterography (MRE). This literature review evaluates recent publications on the role of deep learning...

Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers.

Biosensors & bioelectronics
Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer...

Machine Teaching Allows for Rapid Development of Automated Systems for Retinal Lesion Detection From Small Image Datasets.

Ophthalmic surgery, lasers & imaging retina
Machine teaching, a machine learning subfield, may allow for rapid development of artificial intelligence systems able to automatically identify emerging ocular biomarkers from small imaging datasets. We sought to use machine teaching to automaticall...