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How AI is used in academic publishing of manuscripts?

The main goal of academics is to present their research work in prestigious journals. The process of publishing a paper is a laborious one, and not just competitive. Academic publishers like Elsevier receive about 2.6 million research papers each year. Editors and peer reviewers have to carefully select the most credible research papers for publication.

Manuscript authoring with AI

Manuscript development process is a task that not only includes biomedical statistics and results but also editing, reviewing, and checking content for plagiarism. Although a researcher finds this process lengthy and time-consuming, the effort is worth million-dollar research grants. Most researchers are ESL (English as second language) and need to polish their manuscript for English language errors.

Today, AI tools like Grammarly.com have made polishing of research papers a very simple process. They not only rectify errors related to grammar and punctuation, they also contain sophisticated algorithms to check for terminology in reference to a context. Algorithms are also developed to check for plagiarism of content. These AI tools are software like iThenticate.com.

Manuscript Images with AI

Most biomedical research papers get their scientific integrity from the professional images that they publish. Most images are of microbiology and techniques, such as Western blot. The images are taken from a magnified slide, and this may lead to overlapping of images accidentally. The pictures of these images have to be stored, and their duplication has to be prevented. Careful attention needs to be paid to images as their duplication in papers would get the paper rejected by a journal.

A research paper can contain several sub-images, so researchers now make use of AI to compare all sub-images for authenticity. Duplication of images is avoided with the use of a software that preserves the integrity of images. An automated software named Proofig is an excellent example of AI in manuscript images. This software uses computer vision for scanning a manuscript. Then, all the images are compared within minutes. Any duplication of images is flagged off by this software.

Manuscript review process with AI

A peer reviewer has to carefully parse through the content of the manuscript, identifying the novelty of research and guiding researchers in their work. They also check the accuracy of the results presented in the paper. This is a time-consuming process for many publishers.

ChatGPT is the latest tool of AI and based on the GPT-3 algorithm. It enables a researcher to write a paper efficiently, providing content that is most relevant to the field of study. Now, AI supports the needs of researchers and editors. Scientific research is not completely automated by AI. It needs the efforts of scientists and publishers.

 

 

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Thin layered chromatography (TLC) is now a quantitative analytical method due to the advent of a novel app linked to TLC.

In thin layered chromatography (TLC), an adsorbent material is spread on sheet and components of a mixture get separated due to the effect of the solvent. To determine how pure a sample is or to determine the progress of a chemical reaction, most analytical chemists perform the technique of TLC.

While performing TLC in a laboratory, scientists usually separate components of a black ink or identify all the chemicals present in the extracts of a leaf. This description implies that TLC has been a qualitative technique till date. In other words, it only tells a chemist the different compounds present in a mixture. However, it cannot tell how much quantity of each component is present in the same mixture.

An innovative app named qTLC has been developed by Stefan Guldin. He and his team of researchers use photos taken by a smartphone to decipher the quantity of each component present in a mixture. This implies that qTLC app has to be combined with TLC technique to make it a quantitative and qualitative technique of analysis. Now, compound concentrations can be known through this integrative technique.

In this process, a chemist would place three samples of definite concentration. Next, the chemist would place a sample of unknown concentration. All the four samples have to laid on the TLC plate and the eluting agent has to be run over it. The coloured spots should be dried and visualized in UV light. A smartphone photograph can then be taken for review through the app.

A calibration curve is constructed using the program in the app. The app takes into consideration the spots created by the three samples of known concentration. Then, the unknown concentration of the fourth sample is estimated from the calibration curve.

Uneven illumination is corrected by the app, which is an automated version. Nevertheless, the photos have to very clear and the calibration curve has to be accurate. The size of the spot and the intensity of the spot is also determined accurately by the program. This eliminates error and bias of quantification.

 

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How AI has changed the dynamics of healthcare industry?

 

The healthcare industry has undergone a metamorphosis in recent times. The advent of artificial intelligence has dramatically changed predictive diagnosis and provided personalized plans of treatment, which has in turn improved patient outcomes. The medical processes are now channelized in the right direction. However, we have to consider biomedical ethics of AI in healthcare industry.

The delivery of healthcare goods and services, the procedures associated with diagnostics, and tremendous care offered to patients are some of the avenues being revolutionized by the advent of AI. The power of medical data has never been tapped to this extent by any other technology. Today, AI has transformed the way healthcare professionals deal with electronic patient records, diagnostic tools like imaging techniques, and genetic engineering techniques. Although medical data is vast, AI can easily peruse through it at a very rapid speed. The complexity patterns of medical data have never been understood till date.

As AI has transformed the way of data analysis, diagnosis of patients has become very fast and accurate. Algorithms based on machine learning have been developed and trained on large volumes of medical data of patients. Consequently, the diagnosis of illness can happen at an early stage, improving the outcome of treatments. In fact, personalized treatment plans are now possible due to AI. The prognosis of patients is also improved with AI.

Surgery has now become a mechanical procedure; the entry of medical robots has improved the speed at which surgery can be performed with precision. Medical robots are now assisting surgeons in medical operation theatre. Thanks to robots, minimal invasive procedures are now being performed with ease. The chances of complications are minimized and patients are recovering at a faster rate.

AI has changed the way healthcare processes in call centers are carried. Chatbots are AI-driven health assistants in the virtual world. This has now boosted the prospects of telemedicine. Thanks to digitalization of medical records and chatbots, healthcare delivery services have become very accessible and professionals are now moving beyond confined physical clinics.

Healthcare apps are powered by AI and patients can now manage their diseases by knowing more about their illness in real-time. Patient queries are solved by chatbots and appointments to physicians can also be scheduled as per convenience. Chronic healthcare issues like diabetes have self-care management apps.

In the field of research and development, AI is breaking all barriers. Drug discovery was a laborious process in the field of pharmaceuticals and healthcare. Today, AI tools have algorithms to curtail down the lengthy and costly procedure of drug discovery. AI is now predicting the structures of organic molecules, which are being used later as the active ingredient of a drug. Thus, potential candidates are being devised as novel drugs. The interaction of drugs with biological systems is now better understood with AI tools.

 

 

 

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How to fix flaws of peer review process in academic publishing?

First, let’s enlist the flaws of peer review process in academic publishing: slow and lengthy process, lack of transparency, and slow speed of completion.  As peer review process is a voluntary service, there is sharp shortfall in the number of reviewers working for a journal. Most academics have rigorous workload. Ever since the onset of COVID-19 pandemic, the peer reviewers have ignored academic publishing and the process of academic publishing has hit an all- time low.

Although China has the highest number of papers published in international journals, most journals rely on the work and effort of Western peer reviewers. The quality of science skills offered by American and European peer reviewers is still considered quite high, as compared to Asian countries, like Japan, China, and Korea.

How can the speed of peer review process be increased to boost academic output? Most researchers have told academic publishers that peer review process should be accelerated by paying an honorarium to peer reviewers. Better forms of incentives should be provided to peer reviewers as it is a rigorous process that protects scientific accuracy and establishes facts.

Academic publishers are also asked to share profits with research departments of universities and institutes. Some of the other path-breaking strategies include free subscription of the journal, vouchers of publication, etc. However, peer review process quality lays heavy emphasis on the scientific rigor of reviewers.

If peer review becomes mandatory, universities would only recommend people with outstanding contribution to research. Conflicts of interest is another area that needs to be tackled. If academic publishers create a database of peer reviewers, authors can easily find experts that are related to their field of study.

The recruitment process of peer reviewers should be improved. The type of work academic publishers distribute should also be examined thoroughly. The methodology used in a research study or the content of the novel results should be correlated with the scientific publications of a researcher. Thus, either content or methodology should be used as a criterion for identifying an expert reviewer.

Journals should send vivid invitation letters to selected reviewers, which may or may not be many in number, depending on the field of study. The process is simpler when journal ask reviewers to accept or reject their invitation for review. There are many independent researchers from industries who can ease off the workload of academics. They too must be recruited. Finally, retired professors could form the creamy layer of peer reviewers.

Although double-blind peer review completely negates the biases towards nationalities of researchers, the open peer review process is also gaining ground. The identities of authors and reviewers are disclosed, which makes it a transparent process and increases human communication between authors and reviewers.

Consider the academic review process of Royal Society Open Sciences. It publishes the decisions of the journals editors; it publishes the review letters; and it also requests the voluntary peer reviewers to disclose their identity. The Open Access movement is gaining ground in academic publishing. Greater emphasis is now given to research studies that have time-sensitive parameters.

 

 

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What are the flaws in peer review process of academic publishing?

In academic publishing, an article is first a drafted manuscript that is carefully reviewed by scientists of a particular discipline and specialization. Their in-depth commentary identifies the flaws and highlights the benefits of the experimental study design and results. Receiving research grants and scholarships is impossible without getting a manuscript approved by a group of esteemed peer reviewers, who are usually mid-career researchers with an impressive track record of publications.

Most early career researchers are post-doc candidates who have to scrutinize their work from the eagle eyes of three to four peer reviewers. The authenticity of the research and its related findings need to be officially recognized by peer reviewers. After peer review process is completed, the article is polished by an academic publisher.

Some of the flaws of academic peer review process is that it is a slow and lengthy process, often determined by the type of peer review model followed by a journal. Academics are overworked people and they work on volunteer basis for journals. Therefore, peer review process seems to be exploitative for academics as it offers very little or no remuneration. The time and effort put in reviewing is an integral part of the publication process, so it should be compensated.

Another striking flaw of the peer review process is that is getting biased and lacks transparency. Most journals follow the double blind peer review system. The names of the authors of the manuscript are concealed. The reviewers do not know the names of the authors of the manuscript. At the same time, the names of the reviewers and their credentials are not furnished to authors. Thus, the current system lacks transparency and acts as a “black box.”

Finally, the speed of the peer review process is associated with a long waiting time. Whenever, a paper is submitted to a journal, it is scrutinized for the novelty of findings. Once the content is approved, the authors have to wait for a long time before the paper is sent to set of esteemed peer reviewers.

Once the peer review process is completed, the final publication process is initiated: here, the editors do NOT work in tandem with reviewers. Usually, researchers get their work published in peer-reviewed journals within one year or two.  Delays in peer review process makes policymakers rely on outdated findings of science.

Early career researchers have to make a mark in the field of scholarly publications. They need to get a tenure of post-doc research positions and professorship only on the basis of their successful publications. Most post-doc researchers are very good in laboratory activities. Writing of experimental manuscripts is an art, which needs to be deciphered from the constructive comments of peer reviewers.