AIMC Topic: Humans

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Economic evaluation of a robotic chemotherapy compounding system and its service expansion to network hospital in Thailand.

BMC health services research
BACKGROUND: Robotic systems for chemotherapy preparation offer improved accuracy and staff safety but require substantial capital investment. This study assessed the economic performance of a domestically developed robotic chemotherapy compounding sy...

Exploring doctors' perspectives on precision medicine and AI in colorectal cancer: opportunities and challenges for the doctor-patient relationship.

BMC medical informatics and decision making
BACKGROUND: Precision medicine and artificial intelligence (AI) are increasingly integrated into colorectal cancer (CRC) care, offering personalised treatment strategies and data-driven decision support. While these technologies promise improved outc...

Advances in mass spectrometry of lipids for the investigation of Niemann-pick type C disease.

Lipids in health and disease
Niemann-Pick type C (NPC) disease is a devastating, fatal, neurodegenerative disease and a form of lysosomal storage disorder. It is caused by mutations in either NPC1 or NPC2 genes, leading to the accumulation of cholesterol and other lipids in the ...

Deep learning for tooth detection and segmentation in panoramic radiographs: a systematic review and meta-analysis.

BMC oral health
BACKGROUND: This systematic review and meta-analysis aimed to summarize and evaluate the available information regarding the performance of deep learning methods for tooth detection and segmentation in orthopantomographies.

CYCLONE: recycle contrastive learning for integrating single-cell gene expression data.

BMC bioinformatics
BACKGROUND: Combining single-cell transcriptome sequencing results from several batches reduces batch effect, which improves our understanding of cellular identity and function.

Contrastive learning-driven framework for neuron morphology classification.

Scientific reports
The Neuron morphology classification is a critical task in neuroscience research, as the morphological features of neurons are closely linked to the functional characteristics of neural circuits. However, traditional classification methods often stru...

A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference.

Scientific reports
Medical image analysis using deep learning algorithms has become a basis of modern healthcare, enabling early detection, diagnosis, treatment planning, and disease monitoring. However, sharing sensitive raw medical data with third parties for analysi...

A fully annotated pathology slide dataset for early gastric cancer and precancerous lesions.

Scientific data
Gastric cancer, a significant global health concern, exhibits high morbidity and mortality, especially in advanced stages. Timely diagnosis and intervention are crucial for improving patient outcomes, with Endoscopic Submucosal Dissection (ESD) playi...

AMuCS: Affective multimodal Counter-Strike video game dataset.

Scientific data
Video games are a versatile and multi-faceted stimulus which can elicit complex player experiences. As a consequence, several datasets have been curated or created for studying human cognition, behaviours, and physiological responses where video game...

Refined prognostication of pathological complete response in breast cancer using radiomic features and optimized InceptionV3 with DCE-MRI.

Scientific reports
BACKGROUND: Neoadjuvant therapy plays a pivotal role in breast cancer treatment, particularly for patients aiming to conserve their breast by reducing tumor size pre-surgery. The ultimate goal of this treatment is achieving a pathologic complete resp...