AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Saccharum

Showing 1 to 10 of 12 articles

Clear Filters

Detrimental Effects of Saccharum officinarum Juice on Reproductive Functions of Female Wistar Rats.

Nigerian journal of physiological sciences : official publication of the Physiological Society of Nigeria
Changing dietary compositions have contributed to the growing epidemic of metabolic diseases with serious impacts on several aspects of health, including reproductive health.  Saccharum officinarum juice has a natural sweetness that makes the general...

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.

Scientific reports
Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust re...

Detecting common coccinellids found in sorghum using deep learning models.

Scientific reports
Increased global production of sorghum has the potential to meet many of the demands of a growing human population. Developing automation technologies for field scouting is crucial for long-term and low-cost production. Since 2013, sugarcane aphid (S...

Machine learning for genomic and pedigree prediction in sugarcane.

The plant genome
Sugarcane (Saccharum spp.) plays a crucial role in global sugar production; however, the efficiency of breeding programs has been hindered by its heterozygous polyploid genomes. Considering non-additive genetic effects is essential in genome predicti...

Machine learning for the adsorptive removal of ciprofloxacin using sugarcane bagasse as a low-cost biosorbent: comparison of analytic, mechanistic, and neural network modeling.

Environmental science and pollution research international
Contamination with traces of pharmaceutical compounds, such as ciprofloxacin, has prompted interest in their removal via low-cost, efficient biomass-based adsorption. In this study, classical models, a mechanistic model, and a neural network model we...

Sugarcane disease recognition through visible and near-infrared spectroscopy using deep learning assisted continuous wavelet transform-based spectrogram.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Utilizing visible and near-infrared (Vis-NIR) spectroscopy in conjunction with chemometrics methods has been widespread for identifying plant diseases. However, a key obstacle involves the extraction of relevant spectral characteristics. This study a...

Rapid Classification of Sugarcane Nodes and Internodes Using Near-Infrared Spectroscopy and Machine Learning Techniques.

Sensors (Basel, Switzerland)
Accurate and rapid discrimination between nodes and internodes in sugarcane is vital for automating planting processes, particularly for minimizing bud damage and optimizing planting material quality. This study investigates the potential of visible-...

Robust DEEP heterogeneous ensemble and META-learning for honey authentication.

Food chemistry
Food fraud raises significant concerns to consumer health and economic integrity, with the adulteration of honey by sugary syrups representing one of the most prevalent forms of economically motivated adulteration. This study presents a novel framewo...

Sugarcane leaf disease classification using deep neural network approach.

BMC plant biology
OBJECTIVE: The objective is to develop a reliable deep learning (DL) based model that can accurately diagnose diseases. It seeks to address the challenges posed by the traditional approach of manually diagnosing diseases to enhance the control of dis...

Explainable artificial intelligence-based compressive strength optimization and Life-Cycle Assessment of eco-friendly sugarcane bagasse ash concrete.

Environmental science and pollution research international
Investigations on the potential use of sustainable sugarcane bagasse ash (SCBA) as a supplementary cementitious material (SCM) in concrete production have been carried out. The paper employs model agnostic eXplainable Artificial Intelligence (XAI) to...