Evidence map›Paper›PMID 42787182›Full record

ArticleFrontiers in public health2026

5G/6G mobile telephone technology, methodical progress, pertinent health protection, and artificial intelligence.

Sunil Jain, Prem Kamal Jain

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 authors.

Sunil JainManipal Tata Medical College, Jamshedpur, India.
Prem Kamal JainDepartment of Computer Science & Applied Bioinformatics, Indraprastha Institute of Information Technology, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global mobile data traffic is growing rapidly. Artificial intelligence (AI) plays an important role in this growth, and safety should be a priority in all aspects of this development. Adverse effects on human health with widespread use with upcoming 5G/6G mobile networks need to be addressed. AI with its growing capabilities needs to be explored for safety strategies. We elaborate the AI-based safety measures as 'Conceptual Framework' comprising "3RRs": risk-reducing devices, risk-reducing engineering and environment; and risk-reducing personalization/habits. For devices using frequencies <6 GHz, the electromagnetic field (EMF) exposure measure is in terms of "specific energy absorption rate" for devices using frequencies <6 GHz, the EMF is measured as "absorbed power density." AI is utilized to lower exposure, with sophisticated algorithms analyzing real-time monitoring data. Wireless gadgets used in various fields like mobile communication, health monitoring, exercise monitoring, warfare tele-communications, etc. AI is useful for automating information delivery among multiple smart applications simultaneously and safely, with automatic sequential decision-making in dynamic environments. Engineering environmental safety with reduced radiation is required. The implementation of 6G and future networks, which aim to create a fully connected world, requires dense deployment. This advancement is possible with AI, enabling dynamic deployment, continual adaptation, autonomous decision-making, and robust control systems. Satellite direct-to-device (D2D) communications are only valuable in truly remote areas and in disasters. Personal habits, simple, healthy, safe, enumerated as an 'ABC' plan. AI's capability for real-time data analysis and decision-making can guide users for safe use. Guidance for growth with safety strategies suggested should be useful for progress in engineering, policies of governments', and people's healthy habits proactively.

Indexed as

Artificial IntelligenceCell PhoneWireless TechnologyHumansautomationcommunicationdata analysishabitsradiation nonionizingradiation protectionsmartphonewearable electronic devices

Identifiers

PMID42787182
PMCPMC13601231

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.