AIMC Topic: Female

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Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning.

Parasites & vectors
BACKGROUND: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understanding of their behaviour to devise effective disease control strategies. In this article we show that machine learning can provide a performance assessme...

Factors influencing psychological distress among breast cancer survivors using machine learning techniques.

Scientific reports
Breast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients experience significant distress relating to their diagnosis and treatment. Managing this distress is critical for improving the lifespan and quality of ...

Rapid diagnosis of celiac disease based on plasma Raman spectroscopy combined with deep learning.

Scientific reports
Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, immune, and dietary factors. CD negatively impacts daily activities and may lead to conditions such as osteoporosis, malignancies in the small intestine,...

Advancing equity in breast cancer care: natural language processing for analysing treatment outcomes in under-represented populations.

BMJ health & care informatics
OBJECTIVE: The study aimed to develop natural language processing (NLP) algorithms to automate extracting patient-centred breast cancer treatment outcomes from clinical notes in electronic health records (EHRs), particularly for women from under-repr...

Real-time non-invasive hemoglobin prediction using deep learning-enabled smartphone imaging.

BMC medical informatics and decision making
BACKGROUND: Accurate measurement of hemoglobin concentration is essential for various medical scenarios, including preoperative evaluations and determining blood loss. Traditional invasive methods are inconvenient and not suitable for rapid, point-of...

Exploration and verification a 13-gene diagnostic framework for ulcerative colitis across multiple platforms via machine learning algorithms.

Scientific reports
Ulcerative colitis (UC) is a chronic inflammatory bowel disease with intricate pathogenesis and varied presentation. Accurate diagnostic tools are imperative to detect and manage UC. This study sought to construct a robust diagnostic model using gene...

Machine learning identifies prognostic subtypes of the tumor microenvironment of NSCLC.

Scientific reports
The tumor microenvironment (TME) plays a fundamental role in tumorigenesis, tumor progression, and anti-cancer immunity potential of emerging cancer therapeutics. Understanding inter-patient TME heterogeneity, however, remains a challenge to efficien...

Use of natural language processing techniques to predict patient selection for total hip and knee arthroplasty from radiology reports.

The bone & joint journal
AIMS: To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology ...