AIMC Topic: Humans

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im7G-DCT: A two-branch strategy model based on improved DenseNet and transformer for m7G site prediction.

Computational biology and chemistry
N-7 methylguanosine (m7G) is an important RNA modification that plays a key role in regulating gene expression and cellular physiological functions. Medical research has shown that m7G is closely associated with the development of a variety of diseas...

Novel endometrial receptivity test increases clinical pregnancy and live birth rates in patients with recurrent implantation failure: Secondary analysis of a prospective clinical trial.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVES: This study aimed to evaluate the efficiency of endometrial receptivity testing (ERT) in improving pregnancy outcomes for patients with recurrent implantation failure (RIF), and to investigate the incidence of implantation window displacem...

Enhancing happiness and well-being: AI-driven solutions for accessible, inclusive travel experiences for people with disabilities.

Disability and rehabilitation. Assistive technology
PURPOSE: This study explores the relationship between happiness and well-being, with a particular focus on how Artificial Intelligence (AI) serves as a catalyst for enhancing the quality of life of individuals with disabilities. The research aims to ...

Artificial intelligence in magnetic resonance imaging for predicting lymph node metastasis in rectal cancer patients: a meta-analysis.

European radiology
OBJECTIVE: This meta-analysis aims to evaluate the diagnostic performance of magnetic resonance imaging (MRI)-based artificial intelligence (AI) in the preoperative detection of lymph node metastasis (LNM) in patients with rectal cancer and to compar...

Machine learning-based MRI radiomics to predict postoperative complications following peripheral nerve sheath tumour excision.

The Journal of hand surgery, European volume
This study sought to establish and validate a machine learning-based multi-sequence MRI radiomics model for predicting postoperative complications in patients with peripheral nerve sheath tumours. We conducted a retrospective analysis of 303 patients...

Collaborative twin actors framework using deep deterministic policy gradient for flexible batch processes.

Neural networks : the official journal of the International Neural Network Society
Due to its inherent efficiency in the process industry for achieving desired products, batch processing is widely acknowledged for its repetitive nature. Batch-to-batch learning control has traditionally been esteemed as a robust strategy for batch p...

Broad learning system based on fractional order optimization.

Neural networks : the official journal of the International Neural Network Society
Due to its efficient incremental learning performance, the broad learning system (BLS) has received widespread attention in the field of machine learning. Scholars have found in algorithm research that using the maximum correntropy criterion (MCC) ca...

MRI radiomics combined with delta-radiomics model for predicting pathological complete response in locally advanced rectal cancer patients after neoadjuvant chemoradiotherapy: A multi-institutional study.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
PURPOSE: To construct and validate a magnetic resonance imaging (MRI) radiomics combined with delta-radiomics and clinical information (C) model for predicting pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC...

CMDF-TTS: Text-to-speech method with limited target speaker corpus.

Neural networks : the official journal of the International Neural Network Society
While end-to-end Text-to-Speech (TTS) methods with limited target speaker corpus can generate high-quality speech, they often require a non-target speaker corpus (auxiliary corpus) which contains a substantial amount of pairs to train ...

Adaptive estimation of instance-dependent noise transition matrix for learning with instance-dependent label noise.

Neural networks : the official journal of the International Neural Network Society
Instance-dependent noise (IDN) widely exists in real-world datasets, seriously hindering the effective application of deep neural networks. In contrast to class-dependent noise, IDN is influenced not solely by the class but also by the intrinsic feat...