AIMC Topic: Humans

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Prediction model of acute kidney injury induced by cisplatin in older adults using a machine learning algorithm.

PloS one
BACKGROUND: Early detection and prediction of cisplatin-induced acute kidney injury (Cis-AKI) are essential for the management of patients on chemotherapy with cisplatin. This study aimed to evaluate the performance of a prediction model for Cis-AKI.

[Robot-assisted Total Gastrectomy with D2 Lymphadenectomy and Intracorporal Reconstruction].

Zentralblatt fur Chirurgie
Robot-assisted total gastrectomy for gastric cancer is a demanding operation that is increasingly being performed, not only in Asia but also in specialised centres in Europe. The minimally invasive resection - and above all the lymphadenectomy and th...

Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics.

Journal of ultrasound
AIMS: We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.

Smart Film Actuators for Biomedical Applications.

Small (Weinheim an der Bergstrasse, Germany)
Taking inspiration from the extremely flexible motion abilities in natural organisms, soft actuators have emerged in the past few decades. Particularly, smart film actuators (SFAs) demonstrate unique superiority in easy fabrication, tailorable geomet...

Objective scoring of footpad dermatitis in broiler chickens using image segmentation and a deep learning approach: camera-based scoring system.

British poultry science
1. Footpad dermatitis (FPD) can be used as an important indicator of animal welfare and for economic evaluation; however, human scoring is subjective, biased and labour intensive. This paper proposes a novel deep learning approach that can automatica...

Adopt or Abandon? Surgeon-Specific Trends in Robotic Bariatric Surgery Utilization Between 2010 and 2019.

Journal of laparoendoscopic & advanced surgical techniques. Part A
It is unknown if surgeons are more likely to adopt or abandon robotic techniques given that bariatric procedures are already performed by surgeons with advanced laparoscopic skills. We used a statewide bariatric-specific data registry to evaluate s...

A deep learning radiomics model may help to improve the prediction performance of preoperative grading in meningioma.

Neuroradiology
PURPOSE: This study aimed to investigate the clinical usefulness of the enhanced-T1WI-based deep learning radiomics model (DLRM) in differentiating low- and high-grade meningiomas.

Annual Research Review: Translational machine learning for child and adolescent psychiatry.

Journal of child psychology and psychiatry, and allied disciplines
Children and adolescents could benefit from the use of predictive tools that facilitate personalized diagnoses, prognoses, and treatment selection. Such tools have not yet been deployed using traditional statistical methods, potentially due to the li...