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Field: Cell Image Analysis Techniques

Deep Learning and Transfer Learning for Malaria Detection

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Tayyaba Jameela, Kavitha Athota, Ninni Singh, Vinit Kumar Gunjan et al.

Journal: Computational Intelligence and Neuroscience
Year: 2022
Citations: 56

Infectious disease malaria is a devastating infectious disease that claims the lives of more than 500,000 people worldwide every year. Most of these deaths occur as a result of a delayed or incorrect diagnosis. At the moment, the manual microscope is considered to be the most effective equipment for...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Optimizing brain tumor classification through feature selection and hyperparameter tuning in machine learning models

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Mst. Sazia Tahosin, Md. Alif Sheakh, Taminul Islam, Rishalatun Jannat Lima et al.

Journal: Informatics in Medicine UnlockedYear: 2023Citations: 55

Accurately classifying brain tumors using images is extremely important for prognosis and treatment planning. In this study, we have developed an optimized approach using machine learning techniques to classify brain tumors. Our method involves preprocessing the images, extracting features, selectin...

Life SciencesNeuroscienceNeurologyOpen Access
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Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning

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Debashish Das, Ranitha Vongpromek, Thanawat Assawariyathipat, Ketsanee Srinamon et al.

Journal: Malaria JournalYear: 2022Citations: 53

BACKGROUND: Microscopic examination of Giemsa-stained blood films remains the reference standard for malaria parasite detection and quantification, but is undermined by difficulties in ensuring high-quality manual reading and inter-reader reliability. Automated parasite detection and quantification ...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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Classification of Microscopic Images of Bacteria Using Deep Convolutional Neural Network

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Md. Ferdous Wahid, Tasnim Ahmed, Ahsan Habib

Year: 2018Citations: 52

Classification of bacteria is essential in medical science for diagnosis of numerous diseases, treatment of infection, and trace-back of disease outbreaks. But it takes long time and huge human-effort to manually identify and classify a bacteria. With the advancement of technology, now the task of r...

Life SciencesBiochemistry, Genetics and Molecular BiologyBiophysicsOpen Access
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Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments

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Nuha Bintayyash, Sokratia Georgaka, St. John, Sumon Ahmed et al.

Journal: BioinformaticsYear: 2021Citations: 46

MOTIVATION: The negative binomial distribution has been shown to be a good model for counts data from both bulk and single-cell RNA-sequencing (RNA-seq). Gaussian process (GP) regression provides a useful non-parametric approach for modelling temporal or spatial changes in gene expression. However, ...

Life SciencesBiochemistry, Genetics and Molecular BiologyMolecular BiologyOpen Access
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Sensitive fluorescent microplate bioassay using recombinant Escherichia coli with multiple promoter–reporter units in tandem for detection of arsenic

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Chiaki Tani, Koichi Inoue, Yuri Tani, Md. Harun‐ur‐Rashid et al.

Journal: Journal of Bioscience and BioengineeringYear: 2009Citations: 44

Genetically modified bacterial biosensors can detect specific environmental compounds. Here, we attempted to establish a fluorescent microplate method to detect arsenic using recombinant Escherichia coli cells transformed with plasmids harboring three tandem copies of the ars promoter/operator-the g...

Life SciencesBiochemistry, Genetics and Molecular BiologyMolecular Biology
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GCA-Net : Utilizing Gated Context Attention for Improving Image Forgery Localization and Detection

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Sowmen Das, Md Saiful Islam, Md. Ruhul Amin

Journal: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)Year: 2022Citations: 41

Forensic analysis of manipulated pixels requires the identification of various hidden and subtle features from images. Conventional image recognition models generally fail at this task because they are biased and more attentive towards the dominant local and spatial features. In this paper, we propo...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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Application of Artificial Intelligence in Drug Discovery

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Hitesh Chopra, Atif A. Baig, Rupesh K. Gautam, Mohammad Amjad Kamal

Journal: Current Pharmaceutical DesignYear: 2022Citations: 39

Due to the heap of data sets available for drug discovery, modern drug discovery has taken the shape of big data. Usage of Artificial intelligence (AI) can help to modify drug discovery based on big data to precised, knowledgeable data. The pharmaceutical companies have already geared their departme...

Physical SciencesComputer ScienceComputational Theory and Mathematics
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Automatic brain tumor detection and segmentation from multi-modal MRI images based on region growing and level set evolution

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Ishmam Zabir, Sudip Paul, M. A. Rayhan, Tanmoy Sarker et al.

Year: 2015Citations: 36

Glioma is a type of brain tumor, originates from glial cells. Approximately 80% of them are malignant. Based on pathological evolution of tumor, they can be classified into two types of tumor — high grade & low grade glioma. In this paper, the segmented area obtained from the conventional region-gro...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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ChatGPT or LLM in next-generation drug discovery and development: pharmaceutical and biotechnology companies can make use of the artificial intelligence-based device for a faster way of drug discovery and development

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Soumen Pal, Manojit Bhattacharya, Md. Aminul Islam, Chiranjib Chakraborty

Journal: International Journal of SurgeryYear: 2023Citations: 35

Pal, Soumen PhD; Bhattacharya, Manojit PhD; Islam, Md. Aminul; Chakraborty, Chiranjib PhD Author Information

Life SciencesBiochemistry, Genetics and Molecular BiologyBiophysicsOpen Access
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Combining Deep Convolutional Neural Network with Support Vector Machine to Classify Microscopic Bacteria Images

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Tasnim Ahmed, Md. Ferdous Wahid, Md Jahid Hasan

Year: 2019Citations: 35

Microorganisms such as Bacteria are responsible for the contamination of numerous infectious diseases such as Cholera, Botulism, Gonorrhoea, Lyme disease, Strep throat, Tuberculosis and so on. Therefore, proper identification and classification of bacteria is essential to prevent the outbreak of suc...

Physical SciencesEngineeringMedia Technology
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White blood cells nucleus segmentation from microscopic images of strained peripheral blood film during leukemia and normal condition

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Rakibull Ahasan, Md. Aminur Rab Ratul, A. S. M. Bakibillah

Year: 2016Citations: 31

Counting of White blood cells (WBC) & characterizing their nucleus can provide valuable information to the doctors in order to identify different diseases or stage of a particular disease. The manual method is a tiresome process and has a lot of inaccuracy. On the other hand, the machine (hematologi...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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Automatic segmentation of blood cells from microscopic slides: A comparative analysis

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Deponker Sarker Depto, Shazidur Rahman, Md. Mekayel Hosen, Mst Shapna Akter et al.

Journal: Tissue and CellYear: 2021Citations: 29

With the recent developments in deep learning, automatic cell segmentation from images of microscopic examination slides seems to be a solved problem as recent methods have achieved comparable results on existing benchmark datasets. However, most of the existing cell segmentation benchmark datasets ...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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Tissue Artifact Segmentation and Severity Assessment for Automatic Analysis Using WSI

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Md Shakhawat Hossain, Galib Muhammad Shahriar, M. M. Mahbubul Syeed, Mohammad Faisal Uddin et al.

Journal: IEEE AccessYear: 2023Citations: 27

Traditionally, pathological analysis and diagnosis are performed by manually eyeballing glass-slide specimen under a microscope by an expert. Whole slide image (WSI) is the digital specimen produced from the glass-slide. WSI enabled specimen to be observed on a computer-screen and led to computation...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Hidden Markov model and Chapman Kolmogrov for protein structures prediction from images

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Md. Sarwar Kamal, Linkon Chowdhury, Mohammad Ibrahim Khan, Amira S. Ashour et al.

Journal: Computational Biology and ChemistryYear: 2017Citations: 27

Protein structure prediction and analysis are more significant for living organs to perfect asses the living organ functionalities. Several protein structure prediction methods use neural network (NN). However, the Hidden Markov model is more interpretable and effective for more biological data anal...

Life SciencesBiochemistry, Genetics and Molecular BiologyMolecular BiologyOpen Access
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