AIMC Topic: Humans

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An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.

Scientific reports
Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analysis of this disorder contains various tests, namely ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT). Despite analytica...

Fused federated learning framework for secure and decentralized patient monitoring in healthcare 5.0 using IoMT.

Scientific reports
Federated Learning (FL) enables artificial intelligence frameworks to train on private information without compromising privacy, which is especially useful in the medical and healthcare industries where the knowledge or data at hand is never enough. ...

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Scientific reports
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the aging global population, AD incidence and its socioeconomic burden are increasing. Developing effectiv...

A semi supervised framework for human and machine collaboration in computer assisted text refinement.

Scientific reports
Human writing often exhibits a range of styles and levels of sophistication. However, automated text generation systems typically lack the nuanced understanding required to produce refined and elegant prose. Due to the inherent one-to-many relationsh...

Automated cell annotation and classification on histopathology for spatial biomarker discovery.

Nature communications
Histopathology with hematoxylin and eosin (H&E) staining is routinely employed for clinical diagnoses. Single-cell analysis of histopathology provides a powerful tool for understanding the intricate cellular interactions underlying disease progressio...

Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.

Scientific reports
Neonatal mortality poses a critical challenge in global health, particularly in low- and middle-income countries. Leveraging advancements in technology, such as machine learning (ML) algorithms, offers the potential to improve neonatal care by enabli...

Nuclear morphometrics coupled with machine learning identifies dynamic states of senescence across age.

Nature communications
Cellular senescence is an irreversible state of cell cycle arrest with a complex role in tissue repair, aging, and disease. However, inconsistencies in identifying cellular senescence have led to varying conclusions about their functional significanc...

Cost-effectiveness analysis of robotic exoskeleton versus conventional physiotherapy for stroke rehabilitation in Singapore from a health system perspective.

BMJ open
OBJECTIVES: This study conducted a comprehensive probabilistic cost-effectiveness analysis comparing robotic exoskeleton therapy to conventional physiotherapy for stroke rehabilitation in Singapore, focusing on three patient groups categorised by the...

Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol.

BMJ open
INTRODUCTION: Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, ...

Exploring tuberculosis patients' preferences for AI-assisted remote health management services in China: a protocol for a discrete choice experiment.

BMJ open
INTRODUCTION: Effective health management is critical for patients with tuberculosis (TB), especially given the need for long-term treatment adherence and continuous monitoring. Artificial intelligence (AI)-assisted remote health management services ...