AIMC Topic: Humans

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Automatic classification and prioritisation of actionable BI-RADS categories using natural language processing models.

Clinical radiology
AIM: To facilitate the routine tasks performed by radiologists in their evaluation of breast radiology reports, by enhancing the communication of relevant results to referring physicians via a natural language processing (NLP)-based system to classif...

Development of an automated estimation of foot process width using deep learning in kidney biopsies from patients with Fabry, minimal change, and diabetic kidney diseases.

Kidney international
Podocyte injury plays a key role in pathogenesis of many kidney diseases with increased podocyte foot process width (FPW), an important measure of podocyte injury. Unfortunately, there is no consensus on the best way to estimate FPW and unbiased ster...

Predicting cutaneous malignant melanoma patients' survival using deep learning: a retrospective cohort study.

Journal of cancer research and clinical oncology
BACKGROUND: Cutaneous malignant melanoma (CMM) has the worst prognosis among skin cancers, especially metastatic CMM. Predicting its prognosis accurately could direct clinical decisions.

Group-level brain decoding with deep learning.

Human brain mapping
Decoding brain imaging data are gaining popularity, with applications in brain-computer interfaces and the study of neural representations. Decoding is typically subject-specific and does not generalise well over subjects, due to high amounts of betw...

SNN6mA: Improved DNA N6-methyladenine site prediction using Siamese network-based feature embedding.

Computers in biology and medicine
DNA N6-methyladenine (6mA) is one of the most common and abundant modifications, which plays essential roles in various biological processes and cellular functions. Therefore, the accurate identification of DNA 6mA sites is of great importance for a ...

Validation of a real-time biliopancreatic endoscopic ultrasonography analytical device in China: a prospective, single-centre, randomised, controlled trial.

The Lancet. Digital health
BACKGROUND: Endoscopic ultrasonography (EUS) is a key procedure for the diagnosis of biliopancreatic diseases. However, the performance among EUS endoscopists varies greatly and leads to blind spots during the operation, which can impair the health o...

Revolutionizing drug formulation development: The increasing impact of machine learning.

Advanced drug delivery reviews
Over the past few years, the adoption of machine learning (ML) techniques has rapidly expanded across many fields of research including formulation science. At the same time, the use of lipid nanoparticles to enable the successful delivery of mRNA va...

Data-driven overdiagnosis definitions: A scoping review.

Journal of biomedical informatics
INTRODUCTION: Adequate methods to promptly translate digital health innovations for improved patient care are essential. Advances in Artificial Intelligence (AI) and Machine Learning (ML) have been sources of digital innovation and hold the promise t...

Skill transference and learning curves in novice learners: a randomized comparison of robotic and laparoscopic platforms.

Surgical endoscopy
BACKGROUND: While well-established protocols direct laparoscopic training, there remains a relative paucity of guidelines for robotic education. Furthermore, it is unknown how exposure to one platform influences trainees' proficiency in the other. Th...