AIMC Topic: Machine Learning

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Risk predictions of hospital-acquired pressure injury in the intensive care unit based on a machine learning algorithm.

International wound journal
Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in intensive care units (ICUs) were frequently reported to suffer PIs, with a heavy burden on their life...

A Pilot Study: Detrusor Overactivity Diagnosis Method Based on Deep Learning.

Urology
OBJECTIVE: To develop two intelligent diagnosis models of detrusor overactivity (DO) based on deep learning to assist doctors no longer heavily rely on visual observation of urodynamic study (UDS) curves.

Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

Surgical endoscopy
BACKGROUND: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous thromboembolism regimens as well as outpatient bariatric surgery may increase the risk of postoperat...

AI/ML in Precision Medicine: A Look Beyond the Hype.

Therapeutic innovation & regulatory science
Artificial Intelligence (AI) and Machine Learning (ML) are making headlines in medical research, especially in drug discovery, digital imaging, disease diagnostics, genetic testing, and optimal care pathway (personalized care). However, the potential...

Machine learning methods for predicting protein structure from single sequences.

Current opinion in structural biology
Recent breakthroughs in protein structure prediction have increasingly relied on the use of deep neural networks. These recent methods are notable in that they produce 3-D atomic coordinates as a direct output of the networks, a feature which present...

Active Learning Optimisation of Binary Coded Metasurface Consisting of Wideband Meta-Atoms.

Sensors (Basel, Switzerland)
The design of a metasurface array consisting of different unit cells with the objective of minimizing its radar cross-section is a popular research topic. Currently, this is achieved by conventional optimisation algorithms such as genetic algorithm (...

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery.

Aging
Aging is a complex and multifactorial process that increases the risk of various age-related diseases and there are many aging clocks that can accurately predict chronological age, mortality, and health status. These clocks are disconnected and are r...

Does the Presence of Missing Data Affect the Performance of the SORG Machine-learning Algorithm for Patients With Spinal Metastasis? Development of an Internet Application Algorithm.

Clinical orthopaedics and related research
BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patie...

Terrain Characterization via Machine vs. Deep Learning Using Remote Sensing.

Sensors (Basel, Switzerland)
Terrain traversability is critical for developing Go/No-Go maps for ground vehicles, which significantly impact a mission's success. To predict the mobility of terrain, one must understand the soil characteristics. In-situ measurements performed in t...