AIMC Topic: Female

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Residual breast tissue after robot-assisted nipple sparing mastectomy.

Breast (Edinburgh, Scotland)
INTRODUCTION: While the long-term oncologic safety of robot-assisted nipple sparing mastectomy (RNSM) remains to be elucidated, histologically detected residual breast tissue (RBT) can be a surrogate for oncologically sound mastectomy. The objective ...

The LEukemia Artificial Intelligence Program (LEAP) in chronic myeloid leukemia in chronic phase: A model to improve patient outcomes.

American journal of hematology
Extreme gradient boosting methods outperform conventional machine-learning models. Here, we have developed the LEukemia Artificial intelligence Program (LEAP) with the extreme gradient boosting decision tree method for the optimal treatment recommend...

Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance.

The Lancet. Digital health
BACKGROUND: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT meas...

Prediction of disease progression and outcomes in multiple sclerosis with machine learning.

Scientific reports
Multiple Sclerosis is a chronic inflammatory disease, affecting the Central Nervous System and leading to irreversible neurological damage, such as long term functional impairment and disability. It has no cure and the symptoms vary widely, depending...

Estimating visual field loss from monoscopic optic disc photography using deep learning model.

Scientific reports
Visual field assessment is recognized as the important criterion of glaucomatous damage judgement; however, it can show large test-retest variability. We developed a deep learning (DL) algorithm that quantitatively predicts mean deviation (MD) of sta...

Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning.

Scientific reports
This study aimed to investigate the predictive efficacy of positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) for the pathological response of advanced breast cancer to neoadjuvant chemotherapy (NAC). The b...

A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

Journal of dermatological science
BACKGROUND: Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists' experience and fails to achieve adequate...

Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study.

Journal of medical Internet research
BACKGROUND: Conventional diagnosis of COVID-19 with reverse transcription polymerase chain reaction (RT-PCR) testing (hereafter, PCR) is associated with prolonged time to diagnosis and significant costs to run the test. The SARS-CoV-2 virus might lea...

Predicting risk of dyslexia with an online gamified test.

PloS one
Dyslexia is a specific learning disorder related to school failure. Detection is both crucial and challenging, especially in languages with transparent orthographies, such as Spanish. To make detecting dyslexia easier, we designed an online gamified ...