How do you see AI being helpful in your area of expertise?

As AI tools continue to develop, there is potential to use AI even more in reading medical images, X-rays and scans, diagnosing medical problems and creating treatment plans.

it can offer prompts for patient medication interactions, illnesses present etc

Pre-publication screens of figures and text (iauthenticate, Proofig). Colleagues found it somewhat helpful is Scientific Writing although I do not use AI software to generate texts.

It could help experimental scientists who generate a lot of data, but only share that data via publications. AI might help to cull these results (in inaccessible text+PDF format) to help elucidate new and more effective synthetic procedures from all these papers. Right now, it's up to people to read, but no one can read *everything*. AI should be able to. 

AI is the key element in almost all aspects of autonomous driving, from vision to motion planning, and even control. 

cutting down on arbitrary decisions by regulatory personnel

It has the potential to tie together concepts and identify patterns that require labor intensive reading and thought. 

It can help save time on literature search, for example. 

Being about to scrap the available information from the internet

Nothing at present.

working as a team, not in isolation

I work in robotics and autonomous driving, there is no way to improve without using AI tools.  Cars and robots need to perceive the world accurately and reason about other agents to enable safe interaction.  This is not possible with classical techniques alone, AI tools are our best chance to bring the promise of robotics to reality.

I believe AI will improve some procedures that are too bureaucratic and repetitive

Standardizing procedures and decisions.

May help in making faster diagnosis 

Better prediction algorithms, especially with phenomena that have low base rates (e.g., suicidality)

Allow large datasets to be quickly evaluated and summarized.

It is enormously laborious to search for and read all of the relevant literature for a question.  The AI product can identify key items in the literature that I can then read and confirm relevance and veracity. 

It can improve the overall information crossing among platforms, publications, and patents with the aid of natural language.

In the interpretation of spectroscopic data, and in research search.

Diagnosis of ovarian masses. Diagnostic algorithm. 

analysis, data management

The use of AI algorithms will help us to find new molecules able to be used in the medical field

Reducing time when working with a large amount of data from different omics data.

Being very efficient in finding specific information.
Time-saving in sorting data.
Support in logical reasoning.
Assistance in proofing and writing manuscripts.

interpretation of data

 Machine learning to improve enzyme function in plant systems could be very useful  to increase yields on finite inputs.

One can rough information. Which are not that much helpful 

It will improve structure and also the language fluency
And ultimately the handling and analysis of big data

Collect important data
Make correct analysis. 
Give you ideas for future research. 

Searching patterns of infectión and parasite transmission in function of environmental factors and anthropic forces

To control de patients and diagnostic

It could set up a better diagnosis and management protocol for a certain patient 

Diagnosis 
Risk stratification assessment 

e.g. in protocol writing and/or reporting
or in checking any interactions between medications taken by patients to alert the physician
however the PI/researcher should always be the end reponsible

We can utilise AI to guess the extraction of large pool of novel compounds from plants

alphafold etc

In combing through large data sets to look for patterns.

To predict toxicity of any chemical will decrease the number of animal assay 

It can potentially be beneficial to make the discovery of new therapies more agile and fast, knowledge about the organisms/cellular interactions, etc.

In computational modelling, calculations and designing of new materials.

 It would be of great help in sceintific research desing, summarizining references, writing and editing. However, ethical ligeslation should be accompanying AI. 

Assist in identifying hazards and quantifying risks 

AI can educate patients so they can think logically and practically in maintaining their health and that of society

In mechanisation of production lines, AI can do wonderful job and assist the man power profoundly bye reducing the safety risks as well.

Replacing manual work 

AI is perhaps the most sensitive and efficient technology to detect the earliest changes of biomarkers in heart disease and breast cancer. 

Predict the toxicological effect of a chemical before application in the environment 
Not 

It may Help out in diagnosis processes 

Eliminating mandane tasks. 

Modelling.

I have never used it

yes - for dealing with big data, to ID species fro million of photos, - many useful applications

Can help speed up some analyses

More Speed in paper research and in the manuscript writing

better use for data processing and expediting outputs

AI might greatly help find novel patterns in genomes, metagenomes and in epigenetics. 

It will help getting protocol run. It would also help to put in together many differential  diagnosis . It will be great to see if prolonged video EEG can be sampled easily.  Also would help in getting sense of genetic and metabolic tests to given clinical diagnosis .

In data gathering 

It will enhance critical understanding of pathways, elucidate mechanisms involved in epigenetic, genetics and protein interactions that may ultimately promote personalized medicine.

Ìt can analyze all related data bery fast and find new target for therapy

It could help as an assistant system

Diagnostic and treatment

AI can be helpful in the analysis of big data, which would undoubtedly help scientists identify new therapeutic targets, perform early diagnoses and analyze multiple types of data 

Prediction of expression of certain genes in various tissues.

the context of AI in my expertise is more interesting because this allow me to deeply observe impact of  infectious disease on community and apply prevention methods.

Monitoring patient quality of life measures

Data acquisition, data calibration and environmental modeling 

It could however, help with routine tasks in primary care, like medication refills

Use dataset make forecast estimation

AI would help in saving time as most of the work done manually would require a certain amount of time as compared to AI

Improving diagnostic algorithms, improving Deep brain stimulation and other advanced therapies.

 manage big amount of data

باستخدام الذكاء الاصطناعي، يمكن للصيادلة تتبع تاريخ استخدام المستخدمين، والملاحظة التي تم تسجيلها. ويمكن للذكاء الاصطناعي التنبؤي للحركات غير المنظمة في نظام الدوائي، مما يسمح للصيادلة بالتدخل أن يطلب الأمر.

Automated and real time decision making will optimize food animal production management at the farm level

It will improve the clinical decision making.

AI can be leveraged to answer specific questions, such as identifying covariate effects in pharmacokinetic and pharmacodynamic systems, and automating some aspects of model development.

Automated analysis
many times faster algorithms
this two is already a huge addition to the field

By automating tasks such as data interpretation and image analysis, machine learning liberates researchers to focus on higher-value activities like innovative treatment development and in-depth analyses. 

Can solve many mechanical problems.

AI can help save resources and time in drug discovery
It can also help identifying new drug targets, thus making drug repurposing a good option. Moreover, by its very nature, it can help in analysing the chemical and material space much faster than A/B experiments.

It will provide more opportunities to monitor drug development.

Use of data for policy making rather than subjective approach

It will help in many fields in my area of expertise:
1- When integrated in ultrasound of fetal anomaly scan, it will help clinicians to obtain the adequate views and could draw attention to anomalies
2- When integrated in cardiotocogram during labor, it could be useful in the prediction of hypoxia

Automatically identify patterns in patients speech associated with psychiatric disorders

pattern recognition for counting cells and other subcellular structure
summarizing scientic content of publications

IN ANALYSING COMPLEX PROCESSES TO PRODUCE RELIABLE INDICATORS THAT PREDICT THE SUBSEQUENT FATE OF THE EMBRYO. IE SIMPLIFYING THE COMPLEXITY OF THE EMBRYO

Interpretation of data sets for use in hypothesis mining. 

Writing or discover a problem 

No opinion

It is useful when a lot of data need to be elaborated, provided that that have been checked for appropriateness and relevance

From my point of view, Analytical Chemistry may benefit from AI since it may help predict operating or chemical conditions in the system under analysis. This will be positive for method development since it may help reduce trial assays and costs.

Improve tools used to better understand disease in populations.

Help writing article, find more faster useful information and will help us to find connections between different area

The integration of artificial intelligence (AI) into scientific endeavors has sparked widespread optimism, fueled by its potential to revolutionize research and discovery across various disciplines. AI's ability to process vast amounts of data, identify patterns, and make predictions holds immense promise for accelerating scientific progress. In the field of medicine, AI algorithms can analyze medical images with unprecedented accuracy, aiding in early detection and diagnosis of diseases. Similarly, AI-powered drug discovery platforms can rapidly identify potential drug candidates, significantly reducing the time and resources required to bring new treatments to patients. In astronomy, AI algorithms can analyze astronomical data to identify new celestial objects, map the universe in greater detail, and uncover hidden patterns in cosmic phenomena. AI is also poised to transform materials science, enabling the design of new materials with enhanced properties tailored to specific applications. The transformative potential of AI in science is undeniable, offering a glimpse into a future where scientific breakthroughs are achieved at an unprecedented pace, leading to advancements in healthcare, environmental sustainability, and human understanding of the universe.

it supports easier understanding and access to what is known and what is unknown and what is the gap in the discipline.

Collecting relevant references. Brilliant!

Making it easier to aggregate disparate information.

Increasing efficiency in compiling research and in conducting studies.

It can aid in automating a lot of processes, both in the production and processing. 

It solves complex problems withing a short time

Collection of data, analysis of data

to elucidate mechanistic findings to support scientific evidences 

Make things easier.

I think it will help finding articles and figures related to manuscripts and books that I am writing.

help mainly in language, improve my language mainly in writing scientific field 

Ecological data is often very messy compared to other scientific fields. This is due both to demographic/environmental stochasticity and to inherent difficulties in experimental design/implementation. AI could accellerate the data cleaning and pattern recognition that ecologists are already using machine learning approaches for.

make imaging and pathology diagnoses more efficient.

it helps in matching different chemical combination for specific outcomes.

I have a busy clinical practice and multiple research projects and collaborations with the industry. As english is not my primary anguage it helps me often to rephrase certain parts of text or to help me write grant applications.

Reading chest x-ray
Interpretation of results
Making diagnosis 

I guess you refer to Generative AI as opposed to "classic" AI, where classification and regression tasks are the most usual.

Data acquisition and analysis can be optimized.

Future surgical devices. 

I can't see Ai may be helpful

It is very helpful as it permits gathering a lot of data from, for example, patients databases and analysing it.
However, good criteria is needed in orderr to evaluate if the analyses of the data have been properly perfomed.

It will help to diagnose easy, uncomplicated cases so as to save time which can be channeled to more difficult cases and other activities for career improvement.

Allows the streamlining of most repetitive tasks: editing, rephrasing, simple statistics etc. Helps field officers understand certain tasks.

AI can be used as an diagnostic tool for being fast and accurate assessment of medical images.

Every other sector. 

Identifying areas of risk for potential patients with HCV and recommend screening options by collating list of patient information to be contacted or mailed.

The integration of artificial intelligence (AI) is significantly advance science, particularly in the fields of Neurology and Neuroscience. A noteworthy application is evident in the deployment of AI modeling for the early detection of cognitive decline risk in diseases such as Diabetes. This innovative approach proves highly beneficial in identifying individuals at risk at an early stage, allowing for timely intervention and proactive management. 

Finding potential interactions in large /big datasets

In the field of pathology, diagnosis will be more quicker and accurate with the use of AI.

In the field of radiology, doctors can sometimes overlook lesions. To overcome this, AI-based approaches such as radiogenomics and radiodiagnostics have been developed. Thanks to these approaches, AI can assist radiologists. Moreover, it’s not just that. In a study that I personally developed related to LLM models, we see that even models that have not been specifically developed for radiology can assist diagnostic radiology from certain angles.

Very helpful 

It could help in patient care, perform screening, and allow filtering by clinical severity.

Integration of it in lab machines in solving the errors

Predictive modeling for patients and outcomes

 AI can improve the diagnosis, prognosis, treatment planning, and research of hematological diseases, as well as reduce health disparities and bias in clinical decision-making.

Improve patient management 

Information boost

Improved tracking and modeling of exposures 

In diagnostics; working with known information 

Helping to save lives

Providing access to a summary of the best research in an area from multiple disciplines.  I anticipate that AI will be able to point out problems in published studies/discount those that do not meet quality standards.   Unfortunately, sometimes articles of poor quality are published in reputable journals...and readers who do not understand research or are not critical readers assume that the article is accurate or does not have notable limitations to any generalizabilty because it was published.   Additionally, AI can enhance programming and data analysis work, as well as with data visualizations...and prevent "human error".   

Research, management of patients, organization skills, comunication. Collaboration. 

Increases accuracy of diagnostics 

Managing and exploiting the knowledge base of the field 

Serves as a statiscal tool for modelling

AI could help us in a better care and treatment of our patients.

Analyzing and aggregating research data; Report/clinical notes writing.

Improving diagnosis and optimizing treatment

better diagnosis, accurate measruments

More relevant in reporting the results in a meticulous way. May be once the graphic creation is accessible, better graphical representations of our work can be given using AI

It is helpful in one way to find out the things what I am looking for.