AIMC Topic: Machine Learning

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[Optimization of fermentation processes in intelligent biomanufacturing: on online monitoring, artificial intelligence, and digital twin technologies].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
As a strategic emerging industry, biomanufacturing faces core challenges in achieving precise optimization and efficient scale-up of fermentation processes. This review focuses on two critical aspects of fermentation-real-time sensing and intelligent...

[Machine learning-aided design of synthetic biological parts and circuits].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Synthetic biology is an emerging interdisciplinary field at the convergence of biology, engineering, and computer science. It employs a bottom-up approach to progressively design biological parts, devices, and circuits, aiming to create artificial bi...

[Intelligent mining, engineering, and design of proteins].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Natural components serve the survival instincts of cells that are obtained through long-term evolution, while they often fail to meet the demands of engineered cells for efficiently performing biological functions in special industrial environments. ...

Identifying responders to gabapentin for the treatment of alcohol use disorder: an exploratory machine learning approach.

Alcohol and alcoholism (Oxford, Oxfordshire)
BACKGROUND: Gabapentin, an anticonvulsant medication, has been proposed as a treatment for alcohol use disorder (AUD). A multisite study tested gabapentin enacarbil extended-release (GE-XR; 600 mg/twice a day), a prodrug formulation, combined with a ...

A Hands-On Introduction to Data Analytics for Biomedical Research.

Function (Oxford, England)
Artificial intelligence (AI) applications are having increasing impacts in the biomedical sciences. Modern AI tools enable uncovering hidden patterns in large datasets, forecasting outcomes, and numerous other applications. Despite the availability a...

Mapping intellectual structure and research hotspots of cancer studies in primary health care: A machine-learning-based analysis.

Medicine
In the contemporary fight against cancer, primary health care (PHC) services hold a significant and critical position within the healthcare system. This study, as one of the most detailed investigations into cancer research in primary care, comprehen...

Model development and validation for predicting small-cell lung cancer bone metastasis utilizing diverse machine learning algorithms based on the SEER database.

Medicine
The aim of this study was to devise a machine learning algorithm with superior performance in predicting bone metastasis (BM) in small cell lung cancer (SCLC) and create a straightforward web-based predictor based on the developed algorithm. Data com...

Preoperative prediction of textbook outcome in intrahepatic cholangiocarcinoma by interpretable machine learning: A multicenter cohort study.

World journal of gastroenterology
BACKGROUND: To investigate the preoperative factors influencing textbook outcomes (TO) in Intrahepatic cholangiocarcinoma (ICC) patients and evaluate the feasibility of an interpretable machine learning model for preoperative prediction of TO, we dev...

Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection.

World journal of gastroenterology
BACKGROUND: Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy pro...

Predicting Postoperative Circulatory Complications in Older Patients: A Machine Learning Approach.

Biomedical and environmental sciences : BES
OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients.