AIMC Topic: Artificial Intelligence

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Artificial intelligence with feature fusion empowered enhanced brain stroke detection and classification for disabled persons using biomedical images.

Scientific reports
Brain stroke is an illness which affects almost every age group, particularly people over 65. There are two significant kinds of strokes: ischemic and hemorrhagic strokes. Blockage of brain vessels causes an ischemic stroke, while cracks in blood ves...

Human-alignment influences the utility of AI-assisted decision making.

Scientific reports
Whenever an AI model is used to predict a relevant (binary) outcome in AI-assisted decision making, it is widely agreed that, together with each prediction, the model should provide an AI confidence value. However, it has been unclear why decision ma...

Developing an AI-powered wound assessment tool: a methodological approach to data collection and model optimization.

BMC medical informatics and decision making
BACKGROUND: Chronic wounds (CWs) represent a significant and growing challenge in healthcare due to their prolonged healing times, complex management, and associated costs. Inadequate wound assessment by healthcare professionals (HCPs), often due to ...

Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours.

Scientific reports
This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT) using digitised Haematoxylin and Eosin stained whole-slide images (WSI). Machine learning (ML) classifiers were developed and tested using 320 scann...

Reframing robotics in Mohs surgery for rare cutaneous sarcomas: conceptual promise and clinical realities in precision oncology.

Journal of robotic surgery
Dermatofibrosarcoma protuberans (DFSP) is a rare, locally aggressive cutaneous sarcoma in which achieving histologically negative margins is paramount to minimizing recurrence. Mohs micrographic surgery (MMS) has transformed margin control in DFSP by...

Ai-driven de novo design of customizable membrane permeable cyclic peptides.

Journal of computer-aided molecular design
Cyclic peptides, prized for their remarkable bioactivity and stability, hold great promise across various fields. Yet, designing membrane-penetrating bioactive cyclic peptides via traditional methods is complex and resource-intensive. To address this...

Pediatric surgical trainees and artificial intelligence: a comparative analysis of DeepSeek, Copilot, Google Bard and pediatric surgeons' performance on the European Pediatric Surgical In-Training Examinations (EPSITE).

Pediatric surgery international
OBJECTIVE: Large language models (LLMs) have advanced rapidly, but their utility in pediatric surgery remains uncertain. This study assessed the performance of three AI models-DeepSeek, Microsoft Copilot (GPT-4) and Google Bard-on the European Pediat...

Advanced dynamic ensemble framework with explainability driven insights for precision brain tumor classification across datasets.

Scientific reports
Accurate detection of brain tumors remains a significant challenge due to the diversity of tumor types along with human interventions during diagnostic process. This study proposes a novel ensemble deep learning system for accurate brain tumor classi...

Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling.

Nature communications
Intensive care unit (ICU) patients often experience rapid changes in clinical status, requiring timely identification of deterioration to guide life-sustaining interventions. Current artificial intelligence (AI) models for acuity assessment rely on m...