AIMC Topic: Humans

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Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.

Scientific reports
Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiomics data of STAD patients in The Cancer Genome Atlas (TCGA)-STAD cohort, which included mRNA, microR...

Optimized convolutional neural network using African vulture optimization algorithm for the detection of exons.

Scientific reports
The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still re...

Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax.

Scientific reports
Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI)...

A deep learning based model for diabetic retinopathy grading.

Scientific reports
Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Existing methods to detect this disease often rely on handcrafted features which limit the adaptability a...

Secretary bird optimization algorithm based on quantum computing and multiple strategies improvement for KELM diabetes classification.

Scientific reports
The classification of chronic diseases has long been a prominent research focus in the field of public health, with widespread application of machine learning algorithms. Diabetes is one of the chronic diseases with a high prevalence worldwide and is...

Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study.

Scientific reports
To explore in depth the characteristics of the risk factors for diabetes and prediabetes pathogenesis and progression in special regions. We investigated medical data from 160 thousand cases in the newly developing urban area of a large modern city f...

Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images.

Scientific reports
The most common carcinoma-related cause of death among women is breast cancer. Early detection is crucial, and the manual screening method may lead to a delayed diagnosis, which would delay treatment and put lives at risk. Mammography imaging is advi...

Self-rerouting sensor network for electronic skin resilient to severe damage.

Nature communications
We propose a network architecture for electronic skin with an extensive sensor array-crucial for enabling robots to perceive their environment and interact effectively with humans. Fault tolerance is essential for electronic skins on robot exteriors....

A Rectal Cancer Surgery Dataset: Use of artificial intelligence to aid automation of error identification.

Scientific data
Minimally invasive surgery is complex and prone to variation not routinely objectively measured. We established an association between skills and patient outcomes. The evolving application of artificial intelligence techniques could assist intraopera...

Monolithic electrostatic actuators with independent stiffness modulation.

Nature communications
Robotic artificial muscles, inspired by the adaptability of biological muscles, outperform rigid robots in dynamic environments due to their flexibility. However, the intrinsic compliance of the soft actuators restricts force transmission capacity an...