Evidence map›Paper›PMID 39314890›Full record

ArticleData in brief2024

REMP: A unique dataset of rare and endangered medicinal plants in Bangladesh for sustainable healing and biodiversity conservation.

Mohammad Manzurul Islam, Sanjida Rahman, Nahida Hoque, Md Al Mamun, Md Sultan Moheuddin, Md Sawkat Ali, Mohammad Rifat Ahmmad Rashid, Saleh Masum, Md Hasanul Ferdaus, Nishat Tasnim Niloy and 1 more

Abstract read
In one paragraph

Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Mohammad Manzurul IslamDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Sanjida RahmanDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Nahida HoqueDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Md Al MamunDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Md Sultan MoheuddinDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Md Sawkat AliDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Mohammad Rifat Ahmmad RashidDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Saleh MasumDepartment of Information and Communication Engineering, University of Rajshahi, Bangladesh.
Md Hasanul FerdausDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Nishat Tasnim NiloyDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.
Md Atiqur RahmanDepartment of Computer Science and Engineering, East West University, Aftabnagar, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In Bangladesh, there are significant number of medicinal plants, but currently no comprehensive record of these valuable species is publicly available. Alarmingly, some of these plants are in a precarious state of endangerment. Therefore, we are creating a unique dataset of Bangladesh's rare, endangered, and threatened medicinal plants to support conservation efforts. It will help us to track and conserve endangered plant species, ensuring a more organized approach to research and preservation efforts. We conducted on-site visits to the National Botanical Garden and The Government Unani and Ayurvedic Medical College, capturing photographs of these plants in optimal sunlight conditions at various times of the day. This involved fieldwork, detailed image annotations, dataset organization, diversity augmentation, and contribution to the preservation of our natural heritage. We have collected a total of 16 types of rare and endangered medicinal plant leaf photos to create our unique dataset consisting of a total of 3494 images. This dataset will help researchers in biodiversity conservation through building efficient machine learning models and applying advanced machine learning techniques to identify rare and endangered medicinal plants.

Indexed as

Endangered plantsMachine learningMedicinal plantsRare plantsThreatened plants

Identifiers

PMID39314890
PMCPMC11418000

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.