AIMC Topic: Humans

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Identification and validation of prognostic genes associated with T-cell exhaustion and macrophage polarization in breast cancer.

Frontiers in endocrinology
BACKGROUND: The most frequent malignant tumor in women is breast cancer (BRCA). It has been discovered that T-cell exhaustion and macrophages play significant roles in BRCA. It was necessary to explore prognostic genes associated with T-cell exhausti...

AI-based multimodal prediction of lymph node metastasis and capsular invasion in cT1N0M0 papillary thyroid carcinoma.

Frontiers in endocrinology
BACKGROUND: Accurate preoperative evaluation of cT1N0M0 papillary thyroid carcinoma (PTC) is essential for guiding appropriate treatment strategies. Although ultrasound is widely used for clinical staging, it has limitations in detecting lymph node m...

Development and validation of a LASSO logistic regression based nomogram for predicting live births in women with polycystic ovary syndrome: a retrospective cohort study.

Frontiers in endocrinology
OBJECTIVE: There is limited study on predictive models for live births in patients with polycystic ovarian syndrome (PCOS). The study aimed to develop and validate a nomogram for predicting live births in Chinese women with PCOS, as well as to identi...

Deep learning to promote health through sports and physical training.

Frontiers in public health
BACKGROUND: Physical activity plays a crucial role in maintaining health and preventing chronic diseases. However, accurately assessing the impact of sports and physical training on health improvement remains a challenge. Recent advancements in deep ...

Optimizing phage therapy with artificial intelligence: a perspective.

Frontiers in cellular and infection microbiology
Phage therapy is emerging as a promising strategy against the growing threat of antimicrobial resistance, yet phage and bacteria are incredibly diverse and idiosyncratic in their interactions with one another. Clinical applications of phage therapy o...

Pharmacovigilance in the digital age: gaining insight from social media data.

Experimental biology and medicine (Maywood, N.J.)
Pharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous reporting systems and clinical trials are valuable for identifying adverse drug events, but face de...

Type 2 Diabetes in Taiwan: Unmasking Influential Factors Through Advanced Predictive Modeling.

Journal of diabetes research
Type 2 diabetes (T2D) is influenced by lifestyle, genetics, and environmental conditions. By utilizing machine learning techniques, we can enhance the precision of T2D risk prediction by analyzing the complex interactions among these variables. This...

Neuro-symbolic procedural semantics for explainable visual dialogue.

PloS one
This paper introduces a novel approach to visual dialogue that is based on neuro-symbolic procedural semantics. The approach builds further on earlier work on procedural semantics for visual question answering and expands it with neuro-symbolic mecha...

A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts.

PloS one
Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation since one or more specialists are usually required for image annotation, and creating ground truth l...