AIMC Topic: Humans

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Diagnostics of diabetic retinopathy based on fundus photos using machine learning methods with advanced feature engineering algorithms.

Scientific reports
Diabetes is one of the main diseases posing a threat to healthcare systems. One of the complications of diabetes is diabetic retinopathy, which, if left untreated, can lead to serious consequences such as blindness. Early detection of this disease is...

Hybrid CNN-BLSTM architecture for classification and detection of arrhythmia in ECG signals.

Scientific reports
This study introduces a robust and efficient hybrid deep learning framework that integrates Convolutional Neural Networks (CNN) with Bidirectional Long Short-Term Memory (BLSTM) networks for the automated detection and classification of cardiac arrhy...

Opportunities and Challenges of Using Artificial Intelligence in Predicting Clinical Outcomes and Length of Stay in Neonatal Intensive Care Units: Systematic Review.

Journal of medical Internet research
BACKGROUND: The use of artificial intelligence (AI) in health care has been steadily increasing for over 2 decades. Integrating AI into neonatal intensive care units (NICUs) has promise as it has the potential to reshape neonatal care and improve out...

Deep Learning Algorithms in the Diagnosis of Basal Cell Carcinoma Using Dermatoscopy: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: In recent years, deep learning algorithms based on dermatoscopy have shown great potential in diagnosing basal cell carcinoma (BCC). However, the diagnostic performance of deep learning algorithms remains controversial.

Robotic adrenalectomy: a comprehensive review of perioperative outcomes, comparative efficacy, and technological advancements.

Journal of robotic surgery
The adrenal glands are small but vital endocrine organs responsible for hormone production, which is essential for stress response, fluid balance, and blood pressure regulation. Adrenalectomy, the surgical removal of one or both adrenal glands, is in...

Enhanced retinal blood vessel segmentation via loss balancing in dense generative adversarial networks with quick attention mechanisms.

International ophthalmology
PURPOSE: Manual segmentation of retinal blood vessels in fundus images has been widely used for detecting vascular occlusion, diabetic retinopathy, and other retinal conditions. However, existing automated methods face challenges in accurately segmen...

Activities of Daily Living Detection through Energy Consumption Data and Machine Learning to Support Independent Aging.

Journal of medical systems
The aging population presents significant challenges for healthcare and social services, emphasizing the need for innovative solutions that support independent living. This study explores the feasibility of identifying Instrumental Activities of Dail...

A novel sEMG-based hand gesture prediction method using a new motion detection algorithm and an LCNN model.

Biomedical physics & engineering express
This paper proposes a novel gesture prediction method for accurately predicting hand gesture types from raw sEMG signals in real time. First, we utilize a linear combination of the mean and standard deviation of sEMG signals within a sliding window t...

Histopathological cancer images classification with Deng entropy.

Biomedical physics & engineering express
Histopathological imaging is of paramount importance for the initial detection, diagnosis, and classification of tumors. Recurrent neural networks and convolutional neural networks have led to substantial advancements in digital pathology, thereby en...

Recellularization of scaffolds derived from precision-cut kidney slices.

Biomedical materials (Bristol, England)
The global rise in chronic kidney disease necessitates innovative solutions for end-stage renal disease that can help to overcome the limitations of the only available treatment options, transplantation and dialysis. Tissue engineering presents a pro...