AIMC Topic: Algorithms

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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis
Protein structure characterization is critical for therapeutic protein drug development and production. Drop-coating deposition Raman (DCDR) spectroscopy offers rapid and cost-effective acquisition of vibrational spectral data characteristic of prote...

A Diagnosis-Based Siamese Network for Fault Detection Through Transfer Learning.

Journal of chemical information and modeling
Traditional deep-learning-based approaches often struggle with data imbalance and variability across fault conditions and normal scenarios, especially in industrial processes. Besides, inconsistent feature distributions from combining different fault...

Optimal Descriptor Subset Search via Chemical Information and Target Activity-Guided Algorithm for Antimicrobial Peptide Prediction.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have emerged as a promising alternative to conventional drugs due to their potential applications in combating multidrug-resistant pathogens. Various computational approaches have been developed for AMP prediction, rangi...

CAML: Commutative Algebra Machine Learning─A Case Study on Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling
Recently, Suwayyid and Wei introduced commutative algebra as an emerging paradigm for machine learning and data science. In this work, we propose commutative algebra machine learning (CAML) for the prediction of protein-ligand binding affinities. Spe...

Enhancing Monte Carlo Tree Search for Retrosynthesis.

Journal of chemical information and modeling
Computer-Assisted Synthesis Programs are increasingly employed by organic chemists. Often, these tools combine neural networks for policy prediction with heuristic search algorithms. We propose two novel enhancements, which we call eUCT and dUCT, to ...

[Application and progress of artificial intelligence technology in interventional pulmonology].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
In recent years, interventional pulmonology has advanced rapidly, with bronchoscopy becoming a cornerstone in the diagnosis and treatment of respiratory diseases. The integration of artificial intelligence (AI) technology has established an intellige...

Towards real time efficient and robust ECoG decoding for mobile brain-computer interface.

Journal of neural engineering
. Decoding locomotion-related brain activities from electrocorticographic (ECoG) signals is essential in brain-computer interfaces (BCIs). Most previous ECoG decoders are computationally demanding and sensitive to noises/outliers. Mobile and robust B...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Nanoscale
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...

Prospective quality control in chest radiography based on the reconstructed 3D human body.

Physics in medicine and biology
Chest radiography requires effective quality control (QC) to reduce high retake rates. However, existing QC measures are all retrospective and implemented after exposure, often necessitating retakes when image quality fails to meet standards and ther...

Recent advancements in feature extraction and classification based bone cancer detection - a systematic review.

Biomedical physics & engineering express
Cancer is a deadly disease that occurs due to the uncontrolled growth of abnormal cells. Bone cancer is the third most occurring disease; approximately 10,000 patients suffer from bone cancer in India annually. It can lead to death if not diagnosed i...